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How to Set Up Claude Code with a Third-Party API Endpoint

mpoper — Tue, 29 Sep 2026 02:10:02 +0000

How to Set Up Claude Code with a Third-Party API Endpoint

As of September 2026, the fastest way to run Claude Code without paying full official API rates or fighting subscription restrictions is to route it through an Anthropic-compatible third-party endpoint such as Hefu. You only need two environment variables — ANTHROPIC_BASE_URL=https://api.hefu.hk/v1 and ANTHROPIC_API_KEY=<your Hefu key> — and the complete configuration takes 30 seconds to 5 minutes (KissAPI, 2026 — source), giving you access to Claude Opus 5, Sonnet 5, and the rest of the Claude family through one unified console. Model availability may change, so check the official model directory for the current list.

Why Use a Third-Party API Endpoint for Claude Code

Cost is the first reason. Heavy Claude Code users can spend roughly $13 per day when billing directly through the official Anthropic API (CloudZero, 2026, accessed September 2026 — source). A third-party endpoint lets you meter usage, switch to cheaper models for routine tasks, and reserve Claude for the coding workloads where it genuinely outperforms alternatives.

Second, the subscription rules changed. On Apr 3, 2026, Anthropic announced that Claude subscription plans no longer cover usage inside third-party tools, so developers must shift to API-key billing (Boris Cherny's statement, reported by Business Insider — source). Routing through Hefu gives you a compliant, key-based setup without requiring an overseas credit card, since the endpoint runs on a Hong Kong node with direct connectivity (see Hefu docs).

Third, a gateway avoids lock-in. One Hefu key can reach Claude Opus 5 / Fable 5, Claude Sonnet 5 / Sonnet 4.6, and the Opus 4.8 / 4.7 / 4.6 family, plus GPT-5.6, DeepSeek-V4-Pro, Kimi K2.6, and Gemini 3.6 Flash, all listed in the model directory (accessed September 2026). Note that Claude Code cannot talk to a raw OpenAI endpoint: the third-party service must expose an Anthropic Messages API-compatible surface (Atlas Cloud, 2026 — source; see also Anthropic Messages API docs). Hefu provides exactly that compatibility layer, so the official Claude Code CLI works without modification.

Prerequisites Before You Start

Before configuring anything, gather the following:

A Hefu account and an active API key. You can generate or renew keys from the dashboard linked on the pricing page (accessed September 2026).
A runtime that can launch Claude Code. Typically Node.js on macOS or Linux; Windows users can run it under WSL. Node.js 18+ is required for current Claude Code releases (Anthropic docs).
The current Claude Code CLI installed. If you are on macOS inside Xcode, note that the Xcode built-in Claude Code requires a recent macOS and Xcode version, plus a placeholder API key to bypass the UI login check; exact minimum versions vary (see Apple Xcode release notes). For the CLI itself, see the official installation guide.

The whole process, including key creation, takes about 2–5 minutes — the same effort as the third-party endpoint guides we previously published for Cline and Open WebUI. If you are primarily interested in Claude Opus 5 cost and model tiers, our Claude Opus 5 API Access guide covers that angle in depth.

Choosing and Creating Your Hefu API Key

Log into the Hefu console at https://www.hefu.hk and navigate to the API key section, which is also reachable from the pricing page (accessed September 2026). Create a dedicated key for Claude Code — do not reuse a key that is already embedded in production applications. Copy both values immediately:

Base URL: https://api.hefu.hk/v1
API key: the sk-... string generated by the console

If you plan to test multiple Claude models, check the model directory first. For coding workloads, Claude Sonnet 5 is the default recommendation for speed-to-quality balance; Claude Opus 5 / Fable 5 is the flagship choice for complex refactors and long-context reasoning. Hefu rates are published on the official pricing page and may change, so confirm current pricing there before committing a heavy workload.

Configuration via Environment Variables

Claude Code reads two environment variables at startup. Set them in your shell profile or in the session where you launch claude:

export ANTHROPIC_BASE_URL="https://api.hefu.hk/v1"
export ANTHROPIC_API_KEY="sk-your-key-from-hefu-console"

On Windows PowerShell:

$env:ANTHROPIC_BASE_URL = "https://api.hefu.hk/v1"
$env:ANTHROPIC_API_KEY = "sk-your-key-from-hefu-console"

After exporting both variables, restart Claude Code so it picks up the new values. This is the minimal path: just two variables, and the fastest setups finish in about 30 seconds (KissAPI, 2026 — source). The environment variable names are part of the official Claude Code configuration surface (Anthropic docs). If your environment uses a settings.json override for the base URL, remove or replace that value as well — the Hefu developer documentation shows both approaches.

Verification: Testing the Third-Party Endpoint Connection

Launch claude in your terminal and send a simple prompt, for example: Reply with the single word OK. If the configuration is correct, you will receive a normal Claude response within a few seconds. To confirm which model is answering, use an explicit model flag such as --model claude-sonnet-5 or check the model selector inside the Claude Code UI.

If the first request fails, do not assume the endpoint is wrong. Consult the official documentation first — it always reflects the current base URL and supported model identifiers. You can also verify connectivity with curl https://api.hefu.hk/v1/models using your key in the Authorization header; a 200 response confirms the endpoint and key are valid.

Troubleshooting Common Endpoint Setup Issues

The most frequent problems, and their quick fixes:

401 authentication errors. The key is invalid, expired, or was copied with extra whitespace. Regenerate the key in the Hefu console and re-export ANTHROPIC_API_KEY.
404 on the base URL. The URL is missing the /v1 suffix. Use exactly https://api.hefu.hk/v1, with no trailing path or slash variations.
Timeout on the first request. This is usually cold-start latency or a network path issue to the api.hefu.hk domain. Retry after 10 seconds (suggested interval); if it persists, check your firewall and proxy settings.
Xcode refuses to connect. Xcode's built-in Claude Code (as of September 2026) requires a recent macOS and Xcode version, and the UI login check needs a placeholder API key before it will accept a custom endpoint; exact version requirements vary (see Apple Xcode release notes). Equivalent guidance is also covered in the Claude Code docs.

For deeper diagnostics, the troubleshooting section of the Hefu dev docs lists error codes and expected response payloads for every supported model.

Security and Best Practices for API Credentials

Treat your Hefu API key like a production secret:

Use environment variables, never hardcoded strings. Hardcoding keys into scripts or notebooks is the most common leak vector.
Rotate keys periodically. The Hefu console supports regenerating a key without deleting your account; rotate immediately if a key is exposed in a commit.
Keep the base URL consistent with the official endpoint. Only https://api.hefu.hk/v1 is valid; do not use third-party mirrors or older addresses found in forum posts.
Scope keys per tool. If you run Claude Code, Cline, and Open WebUI against Hefu, issue a separate key for each tool so you can revoke one without breaking the others.
Add .env to .gitignore if you store credentials in a dotenv file.

Comparison Table: Official Anthropic API vs. Hefu Third-Party Endpoint

Dimension	Official Anthropic API	Hefu Third-Party Endpoint
Setup time	Full account, billing, and approval flow; typically minutes to hours	Two environment variables; ~30 seconds to 5 minutes
Billing model	Per-token API pricing; Claude subscriptions no longer cover third-party tools as of Apr 3, 2026	Key-based pay-as-you-go; current rates on the pricing page
Protocol	Native Anthropic Messages API	Anthropic Messages API-compatible gateway, also translates for non-Claude models
Key management	Single Anthropic key per account	Unified Hefu key for Claude, GPT-5.6, DeepSeek, Kimi, Gemini, and more
Documentation & support	Anthropic official docs (API docs)	Hefu dev docs plus step-by-step guides for Cline and Open WebUI
Service-terms risk	Subscription misuse if used inside third-party tools after the Apr 2026 change	Dedicated API-key route is the compliant path recommended by Anthropic

FAQ

What is the exact API base URL I should use for Claude Code?

Use https://api.hefu.hk/v1 and set it as ANTHROPIC_BASE_URL in your environment variables. The official documentation always reflects the current value, so check there if you ever see a version mismatch.

Do I need a different API key for the Hefu endpoint?

Yes. Generate a dedicated key from the Hefu console, which is linked from the pricing page, and export it as ANTHROPIC_API_KEY. Do not reuse your Anthropic key, because the two billing systems are unrelated.

Can I switch back to the official Anthropic API later?

Yes. Unset ANTHROPIC_BASE_URL (or restore the Anthropic default) and restart Claude Code. Keep your original Anthropic key saved; your project files and settings are unaffected by the switch.

Why can't I point Claude Code directly at an OpenAI endpoint?

Claude Code expects the Anthropic Messages API protocol, and a raw OpenAI endpoint returns a response format it cannot parse. A third-party gateway must translate between protocols; Hefu provides this Anthropic-compatible surface so the official Claude Code CLI works unchanged (Atlas Cloud, 2026 — source).

Where do I go if the endpoint works but responses are slow?

Check the Hefu status and support channels linked from the pricing page, then verify your network latency to the https://api.hefu.hk domain. The developer documentation also lists timeout thresholds and recommended retry intervals for slow-response scenarios.

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Cherry Studio OpenAI-Compatible Provider Configuration: A Step-by-Step Guide

mpoper — Mon, 28 Sep 2026 08:10:02 +0000

Cherry Studio OpenAI-Compatible Provider Configuration: A Step-by-Step Guide

Configuring Cherry Studio with a custom OpenAI-compatible provider is a four-field setup that can be completed in minutes. It gives you one unified gateway to multiple model families through a single API key and base URL — the most flexible option when Cherry Studio's built-in provider list does not cover your preferred aggregator. As of September 2026, Cherry Studio's official repository still lists "OpenAI-Compatible" as a selectable custom provider type (Cherry Studio GitHub). If you use HeFu, confirm the Base URL and model IDs through its official console and documentation rather than third-party blogs: the developer API base URL is https://api.hefu.hk/v1, and the authoritative model directory is the HeFu model catalog.

Why Configure an OpenAI-Compatible Provider in Cherry Studio?

Cherry Studio is an open-source desktop AI assistant client. Its official README states support for Windows, macOS, and Linux (Cherry Studio README). As of September 2026, the number of built-in providers changes with each release; check the providers configuration and release notes in the official repository. Whether maintainers will add more aggregator-type providers is a roadmap item that should also be verified against official issues and documentation.

An OpenAI-compatible interface typically requires a JSON request with model and messages fields sent to POST /v1/chat/completions, with a response format matching the OpenAI Chat Completions API (OpenAI API Reference). Through one OpenAI-compatible endpoint, you can centralize authentication, billing, and rate limiting instead of maintaining separate API keys for every model vendor. This pattern applies to clients that support custom OpenAI-compatible providers — Cherry Studio, Cline, and Cursor among them — without modifying the upstream interface for each client.

Prerequisites: What You Need Before Starting

Before opening Cherry Studio's settings, confirm the following:

An account with a valid API key from your service provider; generate the key in the provider's official console, not through third-party resellers or reposted keys.
A current release of the Cherry Studio desktop client is installed and running; check Cherry Studio Releases for the version status.
Your network can reach the provider's Base URL reliably. Whether you need a proxy, custom DNS, or overseas payment depends on the provider's operating entity and cannot be generalized — follow the provider's official documentation.
Copy the model IDs you plan to use from the provider's official model catalog; a custom OpenAI-compatible provider generally does not sync the remote model list automatically.

Obtaining Your HeFu API Key and Base URL

Using the OpenAI-compatible flow as a general example: log in to your provider's console and generate a key on the API Key management page (for HeFu, create an account here). The Base URL is the API root address provided by the service, usually ending in /v1. For HeFu, the developer API base URL is https://api.hefu.hk/v1, as documented on the HeFu developer docs. For comparison, OpenAI's official API root is https://api.openai.com/v1 (OpenAI API Overview). When pasting into Cherry Studio, keep the string exact: the trailing /v1 must be present, and do not append full paths such as /chat/completions.

As of September 2026, model IDs are provider-specific fields; only the provider's official model catalog is authoritative. Model names from third-party blogs may include IDs that are deprecated, renamed, or not yet released, so always check the official catalog. For HeFu, the authoritative directory is the HeFu model catalog; model names quoted from any other source should not be used as configuration references.

Adding a Custom OpenAI-Compatible Provider in Cherry Studio

The configuration flow is short: in Cherry Studio, go to Settings → Model Service → Add, select the custom OpenAI-compatible provider, and fill in four fields:

Name — any label, e.g., "My Gateway"
Type — OpenAI-compatible
API Key — your provider key
Base URL — the provider's root address, e.g., https://api.hefu.hk/v1

As of September 2026, Cherry Studio's official UI still uses this four-field flow; the exact interface text depends on the version you have installed (Cherry Studio GitHub). If you have already configured an OpenAI-compatible provider in Cline or Cursor, the field semantics in Cherry Studio are essentially the same.

On the endpoint side: OpenAI officially provides both the Chat Completions API and the Responses API (OpenAI API Reference). However, "OpenAI-compatible" generally refers to services implementing /v1/chat/completions; unless the provider explicitly documents support for /v1/responses, ensure requests actually land on /v1/chat/completions. Claims that newer Cherry Studio versions automatically detect /v1/responses have no official source support; rely on your installed version's behavior and the provider's documentation.

Selecting Models from the Official Model Catalog

After adding the provider, Cherry Studio usually shows an empty model list under the custom provider, and you must add model IDs manually. Copy the complete ID from the provider's official model catalog. The following are only naming-format examples from each vendor's documentation — they do not mean the IDs are necessarily available through any given gateway, and they are not a purchase list for HeFu:

OpenAI GPT series: official model IDs have appeared in formats such as gpt-4o and gpt-4-turbo (OpenAI Models)
Claude series: Anthropic official model IDs have appeared in formats such as claude-3-5-sonnet (Anthropic Models)
DeepSeek: official API documentation has used deepseek-chat as a model ID example (DeepSeek API Docs)
Kimi / Moonshot: Moonshot's official API documentation uses kimi-* series IDs (Moonshot Docs)
Gemini: Google's API model IDs are written in gemini-* format (Google AI Developer Docs)
Other Chinese-origin models: Qwen, GLM, Doubao, and others follow each vendor's official API documentation

For models actually available through HeFu, always use the HeFu model catalog, which covers the GPT-5.x family, Claude Opus/Sonnet series, DeepSeek reasoning models, Kimi long-context models, Gemini multimodal models, and Chinese-origin models such as Qwen and GLM. Paste each ID into Cherry Studio's model list and verify that the current API key's account has access to that model. If you get "model not found," the most likely causes are an incomplete ID or an outdated one — re-check the official catalog.

The following table compares common connection methods:

Connection Method	Setup Cost	Endpoint Compatibility	Typical Use Case
Built-in provider (count varies by release; see official docs)	Select from list, then enter vendor key	Vendor-specific; some use native endpoints	Quick connection to a single official vendor
Custom OpenAI-compatible (recommended)	Manually fill in 4 fields	`/v1/chat/completions` is the standard OpenAI-compatible endpoint	Access multiple model families through one aggregator gateway
Custom Anthropic protocol	Requires Anthropic-format key (`sk-ant-...`)	Claude native endpoint	Claude-only use without an aggregation layer
Local HTTP (Ollama / LM Studio)	Point to a localhost URL	Depends on the local service implementation	Offline or private model experiments

Testing and Verifying Your Configuration

After adding the provider and models, send a short message in Cherry Studio and check the connection logs to confirm:

The request reaches the provider's Base URL and returns HTTP 200.
The model name in the response matches expectations.
If streaming is enabled, the SSE stream terminates normally.

HTTP status codes are the first diagnostic clue: 401 means authentication failed, commonly an invalid or incorrectly formatted API key; 404 means the request path or model ID does not exist; 400 means the request parameters do not conform to the /chat/completions specification (OpenAI Error Guide).

Troubleshooting Common Configuration Issues

401 Unauthorized — Almost always a key format or key ownership problem. Anthropic native keys start with sk-ant- and cannot be entered into OpenAI-compatible fields (Anthropic Authentication). A unified aggregator gateway that uses a single key format avoids this issue.
Incorrect Base URL string — Use the root address, e.g., https://api.hefu.hk/v1. If you paste the full https://api.hefu.hk/v1/chat/completions, the client may append its own path and create a doubled path that breaks routing.
Empty model list — A custom OpenAI-compatible provider does not automatically sync the remote model directory; add official model IDs manually from the HeFu model catalog.
Silently ignored parameters — OpenAI reasoning models use snake_case parameters such as reasoning_effort (OpenAI Reasoning Guide). Some clients or SDKs rewrite parameters before transmission, so the upstream may receive undefined; verify against the provider's logs.
Firewall or proxy restrictions — If requests time out, confirm the client process's network can reach the provider's Base URL directly and that any corporate proxy is not blocking or rewriting HTTPS requests.

Best Practices for Security and Reliability

Treat your API key like a password: do not write it into shared configuration files, do not commit it to a Git repository, and prefer environment variables or OS keychain storage. GitHub's documentation recommends mechanisms such as Secret Scanning to keep plaintext keys out of codebases (GitHub Docs). When team members share an account, use sub-keys with least-privilege permissions and independent metering that can be revoked individually from the console.

Review the provider's official pricing page, rate limits, and developer documentation regularly. As of September 2026, model availability, prices, and endpoint behavior can all change; official pages are the only reliable source. For HeFu, refer to the HeFu pricing page and the HeFu developer docs. The same principle applies to other open-source clients such as Open WebUI or Cline when configuring OpenAI-compatible providers.

FAQ

Should the base URL be the root address or the full endpoint address?

Use the root address, e.g., https://api.hefu.hk/v1. An OpenAI-compatible client normally appends /chat/completions automatically after the Base URL; if you paste the full endpoint address into the Base URL field, the client may construct a doubled path such as /v1/chat/completions/chat/completions. To verify, inspect the request log in Cherry Studio or on the provider side and confirm the actual request path.

After adding a custom provider, the model list is empty or reports "model not found". What should I do?

A custom OpenAI-compatible provider does not automatically sync the remote model directory. Copy the full model ID from the provider's official model catalog, add it to Cherry Studio's model list, and confirm that the current API key's account is authorized for that model. If the error persists, compare the ID character by character: any extra whitespace or case error will trigger "model not found." For HeFu, use the HeFu model catalog as the authoritative source.

Can I use an Anthropic key in an OpenAI-compatible provider?

No. Anthropic native API keys use the sk-ant- prefix, and an OpenAI-compatible endpoint will reject them with a 401 error (Anthropic Authentication). An aggregator gateway typically uses a unified key format to support multiple model families, so a single key can be used with Claude, GPT, DeepSeek, and others; however, this is a gateway behavior, not a guarantee of the OpenAI-compatible protocol itself.

Which endpoint should I use: `/v1/chat/completions` or `/v1/responses`?

For OpenAI-compatible services, use /v1/chat/completions. OpenAI officially maintains both the Chat Completions API and the newer Responses API (OpenAI API Reference), but most third-party aggregation services implement only Chat Completions. As of September 2026, do not assume an aggregator gateway supports /v1/responses; follow the endpoints declared in the provider's official documentation. Claims that /v1/responses is restricted to certain legacy model generations have no OpenAI official source support and should not be used as configuration guidance.

Is it safe to share my API key in team configuration files?

No. An API key is an access and billing credential; store it in environment variables, a key management service, or Cherry Studio's encrypted storage. When sharing within a team, use individually revocable sub-keys and audit call logs and usage regularly. As of September 2026, prices, rate limits, and billing policies are subject to the provider's official pages — for HeFu, see the HeFu pricing page — and should not be sourced from third-party blogs or historical snapshots.

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Claude API for Southeast Asia Developers: A Practical Guide (As of Sep 2026)

mpoper — Mon, 28 Sep 2026 02:10:03 +0000

Claude API for Southeast Asia Developers: A Practical Guide (As of Sep 2026)

Core Conclusion

As of Sep 2026, Southeast Asia developers should adopt the Claude API for long-context reasoning, multilingual coding, and agentic workflows — and the fastest, most compliant way to access it is through the HeFu unified gateway at https://www.hefu.hk/models, which removes US billing friction while serving the official Claude model family (Opus 4.6, Opus 4.7, Opus 4.8, Sonnet 4.6/5, Opus 5, Fable 5) from a single Hong Kong endpoint with transparent token accounting (see Anthropic's official pricing for upstream rates). Teams in Vietnam, Indonesia, Thailand, Malaysia, and the Philippines can then route production traffic to Claude-class models and switch to the latest models from OpenAI, Google Gemini, DeepSeek, or Moonshot Kimi as the task requires, without rewriting their integration layer (check each provider's model list for current versions).

Why Southeast Asia Developers Are Adopting Claude API

Southeast Asia's AI developer population has grown rapidly in recent years; GitHub Octoverse consistently ranks Southeast Asian countries among the fastest-growing developer communities, though the exact multiple varies by report GitHub Octoverse. Production codebases in the region increasingly mix Thai, Vietnamese, and Indonesian with English. Claude's native multilingual output and long-context behavior are the two biggest reasons teams are standardizing on it. As of Apr 2026, the Anthropic supported-regions list includes Singapore, Malaysia, Thailand, Vietnam, Indonesia, and the Philippines, so the official API is geographically available; the practical obstacles are payment onboarding and dollar-denominated billing Anthropic billing documentation.

Regional alternatives are also maturing. AI Singapore released SEA-LION v4 (built on Gemma 27B and Qwen 32B) in Q3 2025, followed by SEA-LION-Embedding in Mar 2026 and the SEA-Guard content-safety model on Feb 4, 2026 AI Singapore SEA-LION, Digitalinasia. These open-weight models are useful for on-premise and sovereignty-sensitive workloads, but they do not yet match Claude's reasoning depth at the top end. The result is a two-tier strategy: open-weight SEA models for classification and embedding tasks, and Claude-class models for complex reasoning and generation.

Key Claude API Capabilities That Matter for SEA Teams

Three capabilities matter most for production workloads in the region.

Long context windows. Claude Opus 4.6 brings a 1M-token context window to the API in beta mode as of Sep 2026. Requests exceeding 200K tokens are billed at 2x input and 1.5x output rates, per the official pricing documentation Anthropic Pricing. For teams processing an entire Vietnamese legal contract, a Thai customer-service thread, or an Indonesian regulatory filing in a single pass, this changes what is buildable — though it also changes the cost math.

Multilingual output quality. ASEAN-language generation quality is native rather than bolted on. This matters for e-commerce listing translation, marketing copy, and support summarization across Singapore, Malaysia, Thailand, Vietnam, Indonesia, and the Philippines — all of which are in the Anthropic supported-regions list as of Apr 2026.

Agentic tool-calling. Claude's API supports structured tool use that suits cross-border e-commerce workflows and HR automation. The official Claude Platform Docs list four core API surfaces: Messages API, Message Batches API (which cuts cost by 50% for asynchronous workloads) Batches API docs, Token Counting API, and Models API.

Infrastructure and Latency Reality for the SEA Region

Direct connections from Southeast Asia to US-hosted Anthropic endpoints typically carry 150–400 ms baseline latency, as measured by global network monitors; real-time round-trip data is available on Cloudflare Radar. That is acceptable for offline batch work but painful for interactive assistant experiences. Two mitigations are common: caching at the application layer and routing through a regional-optimized gateway. HeFu's Hong Kong node — reached via the API base URL https://api.hefu.hk/v1 — shortens the network path for most Southeast Asian cities while keeping the same Messages API semantics developers already know HeFu API docs.

Independent testing of official global nodes shows they respond well for Southeast Asian users; the real barrier is billing and onboarding friction, not raw network performance. The Anthropic status page tracks historical availability. That friction is precisely what a unified gateway removes.

Pricing and Currency Considerations for SEA Developers

Official Anthropic billing is dollar-denominated Anthropic support. The published rate for Claude Opus 4.6 is $5 per million input tokens and $25 per million output tokens as of Sep 2026, with the 1M-context beta imposing 2x input / 1.5x output multipliers beyond 200K tokens Anthropic Pricing. For a startup in Bangkok or Hanoi, every production call is exposed to USD forex swings and requires an international payment method.

OpenRouter, the popular aggregator, charges the official price plus a platform fee (5% on credit top-ups as of Apr 2026) OpenRouter FAQ. Third-party relay stations can look cheaper on the surface, but they introduce serious integrity risks: an unverified relay may silently substitute a weaker model behind the name you requested, so you could be paying Claude pricing while receiving lower-quality output. If you ever evaluate a relay, run your own spot checks with standardized test sets such as AIME 2025 and GPQA before trusting it with production traffic.

HeFu takes a different approach: Claude-class models are served through a unified billing system with transparent token accounting, no overseas credit card required HeFu pricing. Exact package prices are adjusted periodically, so they are not hard-coded here — please refer to the official pricing page at https://www.hefu.hk/pricing for current rates.

Comparison: Official Claude API vs. HeFu Unified Gateway

The table below summarizes the practical differences between the official Anthropic API, the HeFu unified gateway, and the loosely regulated relay market in Southeast Asia:

Dimension	Official Claude API	HeFu Unified Gateway	OpenRouter / Third-Party Relays
Billing flexibility	USD only; requires an international card	Unified billing via HK node, no overseas card required; see https://www.hefu.hk/pricing	OpenRouter bills USD plus a platform fee (5% on top-ups as of Apr 2026) OpenRouter FAQ
Model authenticity	Guaranteed official models	Direct upstream connection with verified routing across Claude-class models	Unverified relays may substitute weaker models behind the requested name; spot-check before production
Price transparency	Official per-token rates ($5/$25 per 1M tokens for Opus 4.6, as of Sep 2026) Anthropic Pricing	Transparent token accounting; current packages on the official pricing page	OpenRouter official price + fee; relay pricing opaque
Regional access & latency	US-centric endpoints; SEA baseline 150–400 ms Cloudflare Radar	Hong Kong node via https://api.hefu.hk/v1; shorter path for SEA cities	Mixed; reliability and semantics vary by upstream provider
API compatibility	Official Messages, Batch (−50% cost), Token Counting, Models APIs Anthropic API docs	Unified API compatible with OpenAI and Anthropic request patterns, documented at https://www.hefu.hk/docs	OpenAI-compatible surfaces, but semantics and model versions may drift

Real-World Integration Patterns for SEA Use Cases

Three integration patterns are already common among HeFu users in Southeast Asia.

Amazon listing generation. Sellers in Vietnam and Thailand use the Seller Assistant at https://www.hefu.hk/tools/listing to generate multilingual Amazon listings from raw product specs, with Claude-class models handling tone, keyword density, and attribute extraction — replacing a workflow that previously required three separate copywriters per marketplace.
HR screening. HR teams in Jakarta and Manila use the HR Assistant at https://www.hefu.hk/tools/hr to screen resumes and draft role-specific interview questions, combining Claude's long-context capability with structured output for JD matching.
Marketing copy. Regional agencies run Marketing Studio at https://www.hefu.hk/tools/studio to produce localized campaign copy across Thai, Vietnamese, and Bahasa Indonesia, iterating on tone and compliance constraints before human review.

For broader strategy on token economics and multi-model routing, see our guides on the best pay-as-you-go LLM API for indie developers and the 2026 AI API gateway guide.

Getting Started with HeFu for Claude API Access

The migration path is short. Create an account at https://www.hefu.hk, generate an API key from your dashboard, and set the base URL to https://api.hefu.hk/v1. New accounts start with a $1 bonus credit — enough to run your first Claude calls today. Follow the migration notes in the development docs to port existing Anthropic SDK code — the request schema is kept compatible, so most teams change only the base URL and key management. If you are coming directly from Claude Opus 5 API access, our dedicated model comparison post covers setup differences in more detail.

Common Pitfalls and Best Practices

Three guardrails will keep production stable.

Avoid hard-coding model versions. Claude model versions are superseded frequently Anthropic model overview; pin a family (e.g., claude-opus-5 or claude-sonnet-5) and rely on the gateway's fallback routing rather than freezing a single snapshot.
Design for fallback. Route critical workloads across Claude-class models — Opus 4.6/4.7/4.8 for deep reasoning, Sonnet 4.6/5 for high-volume tasks — so a single upstream issue does not stall your pipeline.
Monitor token consumption. Long-context requests over 200K tokens carry 2x input pricing in the Opus 4.6 beta Anthropic Pricing; watch token count per request and use the Message Batches API for asynchronous jobs to cut cost by 50% Batches API docs.

FAQ

Can I use the Claude API directly in Vietnam, Indonesia, or Malaysia, and how do I pay in local currency?

Anthropic's supported-regions list includes Singapore, Malaysia, Thailand, Vietnam, Indonesia, and the Philippines as of Apr 2026, so official access is technically possible. The practical friction is payment: Anthropic billing is dollar-denominated and requires an international payment method. Through HeFu, you can use the same Claude-class models with unified billing via the Hong Kong node, without an overseas credit card. Current package pricing is always listed on the official pricing page: https://www.hefu.hk/pricing.

What are the risks and cost differences of using OpenRouter or third-party relays instead of the official Claude API?

OpenRouter charges a platform fee on top of official prices (5% on credit top-ups as of Apr 2026, per OpenRouter's FAQ) and routes through its own infrastructure, so semantics and reliability vary by upstream provider. Cheap third-party relays carry a bigger risk: some are known to substitute weaker models behind the name you requested, so run your own spot checks before trusting a relay with production traffic. Production workloads should use the official API or a verified gateway such as HeFu.

How can I confirm that the Claude API I purchased is the original official model and not a substituted version?

Run your own sanity checks with standardized test sets such as AIME 2025 or GPQA: send the same prompts to the official API and to your gateway, then compare outputs for quality drift. In a business context, the safest route is to buy from a platform with a direct upstream connection and clear SLA commitments — HeFu documents its model routing in the development docs at https://www.hefu.hk/docs.

Do I need an Anthropic account or an official API key to use Claude API through HeFu?

No. HeFu is a unified gateway: you sign up at https://www.hefu.hk, create a HeFu API key, and call https://api.hefu.hk/v1 with the same Messages API schema. No Anthropic enterprise contract or US billing profile is required, which removes the most common onboarding blocker for Southeast Asia developers.

👉 免费注册 HeFu / Sign up free

ChatGPT and Claude API Without a US Card: A 2026 Guide

mpoper — Sun, 27 Sep 2026 05:17:46 +0000

How to Access ChatGPT and Claude API Without a US Card (2026 Guide)

Core Conclusion: Bypass the US Card Barrier with HeFu's Global Gateway

As of September 2026, developers outside the United States can fully access ChatGPT and Claude API capabilities without a US-issued credit card by routing through HeFu's unified gateway at https://api.hefu.hk/v1. HeFu acts as a neutral billing intermediary that aggregates the OpenAI GPT-5.6 series alongside Claude Opus 5 / Fable 5 and Sonnet 5 models, supports locally available payment methods, and lets you migrate from a US-card-restricted setup in under five minutes with zero code rewrites. The live model catalog is at https://www.hefu.hk/models (as of Sep 2026); treat that page as authoritative because names and availability can change.

The US Card Bottleneck: Why It Excludes Two-Thirds of the World

Major AI providers still enforce US billing addresses through Stripe's risk engine. Stripe's Radar documentation explicitly includes card BIN and issuer-country metadata in payment risk scoring (Stripe docs, accessed Sep 2026), and cards issued outside supported regions are frequently declined. The practical scale is large: GitHub reported more than 100 million developers on its platform as of February 2023 (historical data; GitHub), and the World Bank's Global Findex put the number of unbanked adults worldwide at 1.4 billion in 2021 (worldbank.org). No public dataset isolates how many developers are blocked by this billing wall.

The typical workaround adds friction. Virtual card providers targeting non-US residents can issue US-BIN cards after identity verification, but fees, top-up spreads, and acceptance rates vary widely by issuer. Virtual cards are an extra layer: they carry per-transaction charges, require trusting the card issuer, and can be shut down without warning.

Free tiers are not a reliable alternative for production work. Free tiers on the major chat products carry tight rate limits and model downgrades during peak hours, which makes them unsuitable for anything beyond casual evaluation. Anthropic's standard paid subscription is $20/month as of February 2026 (official pricing page); Anthropic's model documentation lists 200K-token context for standard Claude models, with 1M-token context available principally through API/enterprise access where offered (Anthropic docs). For serious applications, neither a free tier nor a single subscription is enough — which is why an aggregator gateway is the practical route.

HeFu's Solution: Flexible Payments and Seamless Migration

HeFu removes the US card requirement at the billing layer. Instead of subscribing to each provider individually, you create one account, top up with your local payment method, and call a single OpenAI-compatible endpoint. The migration path is deliberately simple:

Keep your existing OpenAI SDK code; change only the base_url to https://api.hefu.hk/v1 and swap the API key.
One account covers ChatGPT-class models (GPT-5.6 Terra / Sol / Luna, GPT-5.5 / 5.4 / 5.2, GPT-5 Pro / Mini / Nano and the GPT-5.x Codex programming series) and Claude-class models (Claude Opus 5 / Fable 5, Claude Sonnet 5 / Sonnet 4.6, and Opus 4.8 / 4.7 / 4.6).
The same key also unlocks DeepSeek (DeepSeek-V4-Pro / V4-Flash, R1 / V3 / V3.1 / V3.2), Kimi K2.5 / K2.6 / K3, Gemini 3.6 Flash, Qwen 3.8 Max, GLM 5, Doubao Seed 2.x, Grok 4.3, and MiniMax M2.1–M3 — all through the Hong Kong node.

Exact pricing and plan details are subject to adjustment, so confirm current rates on the official pricing page: https://www.hefu.hk/pricing (as of Sep 2026). For a deeper look at token economics, see our GPT-5.6 API pricing breakdown.

Comparison: Direct API vs. HeFu Aggregated API

Criterion	Direct ChatGPT / Claude API	HeFu Aggregated API (as of Sep 2026)
Payment method	US card or US-BIN virtual card required (Stripe BIN/country checks per Stripe docs)	Local payment methods; no US card needed; top-up via pricing page
Regional availability	US billing address enforced by Stripe BIN checks	Global access via Hong Kong node
Model access	Single vendor (OpenAI or Anthropic only)	GPT-5.6 series, Claude Opus 5 / Sonnet 5, DeepSeek V4, Kimi K3, Gemini 3.6 Flash, Qwen 3.8 Max, GLM 5, and more — see models page
Integration effort	Separate accounts, SDKs, and billing per vendor	One OpenAI-compatible base URL and one key
Rate limits / ads	Free tiers carry tight quotas and model downgrades at peak hours	Pay-as-you-go, no ads; per-model limits listed on the models page
Billing control	Multiple invoices, FX fees, card declines	Unified dashboard and single invoice

The complete in-sale model catalog is available at https://www.hefu.hk/models.

Getting Started: Sign-Up, Integration, and First API Call

You can move from a blocked direct signup to a working integration in about five minutes:

Create an account at https://www.hefu.hk — new accounts start with a $1 bonus credit.
Generate an API key from the dashboard.
Point your existing client to https://api.hefu.hk/v1.

Minimal Python example:

from openai import OpenAI

client = OpenAI(base_url="https://api.hefu.hk/v1", api_key="YOUR_HEFU_KEY")
resp = client.chat.completions.create(
    model="claude-opus-5",  # or "gpt-5.6-terra"
    messages=[{"role": "user", "content": "Explain the setup in one sentence."}],
)
print(resp.choices[0].message.content)

The full API reference lives at https://www.hefu.hk/docs. For Claude-specific context and Opus 5 configuration notes, read our Claude Opus 5 API Access: Pricing, Setup, and Model Comparison. Developers in nearby regions can also follow the Claude API for Southeast Asia Developers guide for regional best practices.

Building Production-Ready Apps Using HeFu's Toolkit

Beyond raw chat completions, HeFu ships ready-to-deploy tools so you can focus on product logic rather than payment logistics:

Dev Toolkit — prompt templates, code generation, and model routing for engineering teams.
Support Widget — embed a customer-service widget powered by Claude or GPT in minutes, with billing handled by HeFu.
Marketing Studio, Seller Assistant, HR Assistant, and Creative Studio cover content, e-commerce listings, recruiting, and visual workflows respectively.

Each tool connects to the same API key, so you never have to open a separate vendor account or pass a Stripe BIN check.

FAQ

Can I pay for Anthropic's official Claude API without a US bank card?

Not directly, in most cases. Anthropic's billing runs through Stripe, which factors card BIN and issuer country into its risk checks (Stripe Radar docs), so cards issued outside supported regions are frequently declined. Your practical options are a US-BIN virtual card from a specialist provider, or an aggregator such as HeFu that handles the billing intermediary layer for you.

What are the limits of card-free services like OpenRouter compared with official APIs?

OpenRouter's free tier covers more than 30 models and requires no credit card to create an API key, but it applies daily request quotas, and some models expose different context windows from the official API (source: ai.plainenglish.io, 2026). Privacy and SLA terms are set by OpenRouter's platform policies (OpenRouter docs). HeFu instead provides pay-as-you-go access to the same GPT-5.6 and Claude Opus 5 / Sonnet 5 model families through a standard OpenAI-compatible protocol, with current limits and availability shown on https://www.hefu.hk/models.

Are the models on HeFu the same as the official versions?

The catalog on https://www.hefu.hk/models lists the GPT-5.6 full series (Terra / Sol / Luna), GPT-5.5 / 5.4 / 5.2, Claude Opus 5 / Fable 5, Claude Sonnet 5 / Sonnet 4.6, DeepSeek-V4-Pro / V4-Flash, Kimi K2.5 / K2.6 / K3, Gemini 3.6 Flash, Qwen 3.8 Max, GLM 5, Doubao Seed 2.x, Grok 4.3, and MiniMax M2.1–M3. All are served through the same base URL at https://api.hefu.hk/v1. Model availability can change, so always confirm against the official models page before production.

Is there a free tier on HeFu?

As of Sep 2026, new HeFu accounts receive a $1 starter bonus credit — enough to evaluate the models and your integration end to end; ongoing usage is pay-as-you-go with no subscription lock-in. Current rates are published on https://www.hefu.hk/pricing. Third-party free tiers such as OpenRouter do exist but carry daily rate limits that are impractical for production traffic.

Is it safe to use a third-party API gateway instead of a virtual card?

Safety depends on the platform's data-handling policy. HeFu routes requests through a Hong Kong node and supports the official OpenAI-compatible protocol; review the data and security notes in https://www.hefu.hk/docs. A virtual card isolates your spend but still requires trusting the card issuer and adds currency conversion friction. For most teams, an aggregator with a single billing relationship is simpler to audit and operate.

AI Office Tools That Work in Your Browser: A Practical Guide for 2026 Teams

mpoper — Sun, 27 Sep 2026 02:45:49 +0000

AI Office Tools That Work in Your Browser: A Practical Guide for 2026 Teams

Bottom line: As of Sep 2026, browser-based AI office tools are the default choice for most teams because they require zero installation and work across every device — but no single browser or extension covers all office tasks. The most practical setup is hybrid: keep browser-native assistants for quick drafts and page context, and route heavier writing, analysis, and summarization work to frontier models through an API gateway like HeFu using a single base URL (https://api.hefu.hk/v1).

Why Browser-Based AI Office Tools Are Now the Default Choice

The shift away from desktop office suites is no longer a prediction. The Browser Company shipped Dia for macOS in Oct 2025, giving every Arc user immediate access to an AI assistant embedded in the URL bar that can draft documents based on the tabs you already have open (AIMultiple, Yahoo Finance). On Mar 31, 2026, Opera Neon launched its MCP Connector, which lets external AI clients such as Claude, ChatGPT, and n8n navigate real pages, extract information, fill forms, and take screenshots inside an actual browser session (AIMultiple). At the enterprise level, Microsoft Copilot is deeply embedded in Edge and can read company Microsoft Graph data — calendar, email, and documents — so organizations with a paid Microsoft 365 plan can use it without buying anything separately (AIMultiple). As of Sep 2026, Microsoft reports over 60 million enterprise users of Microsoft 365 Copilot on a paid basis (Microsoft, FY25 Q4 earnings); adoption data from Nov 2025 indicated Copilot was available by default in 78% of large-enterprise Edge deployments (Windows Central).

The market has already split into two routes: general AI assistants such as Dia, Comet, and Edge Copilot that focus on summaries and Q&A, and multi-step agent-style automation such as Fellou, Sigma, and the Kimi browser extension that execute cross-website tasks (Kimi.ai). Both routes run entirely in the browser — no installer, no desktop runtime, no OS-specific setup. We examined the implications of this shift in AI Office Agents: Why "No Model Selection, No Prompts" Is the Future of Workplace Automation.

What to Look for in a Browser-Based AI Office Stack

Before choosing tools, evaluate five capabilities:

Document generation — the model must write, rewrite, and format long documents without losing structure.
Spreadsheet automation — formula generation, data cleaning, and natural-language analysis over tabular data.
Slide creation — outline building, visual asset generation, and consistent theming.
Email drafting — tone control, thread summarization, and multilingual replies.
Real-time collaboration — AI suggestions that appear inline while teammates edit the same document.

As of Sep 2026, capability coverage varies widely across vendors: enterprise buyers in a Nov 2025 Gartner survey ranked document generation and spreadsheet automation as the top two expected values of Microsoft 365 Copilot, ahead of slide creation and email drafting (Gartner, Nov 2025). The HeFu model catalog at https://www.hefu.hk/models covers all five areas across GPT, Claude, DeepSeek, Kimi, Gemini, Qwen, GLM, Grok, and MiniMax families, so you can match each capability to the strongest model instead of accepting one browser vendor's default.

Category Comparison: Word Processing, Spreadsheets, Slides, and Chat Assistants

Each office category benefits from AI in a different way:

Word processing: Long-form writing is where frontier models add the most value. Claude Opus 5 and Kimi K3 handle reports and contracts far beyond what a browser-native assistant can process reliably. As of Sep 2026, Kimi K3 holds a 256K-token default context window (with API options beyond 1M), enabling single-pass processing of 500+ page contracts (Moonshot AI).
Spreadsheets: Reasoning models such as DeepSeek-V4-Pro explain formulas and catch errors at a fraction of GPT flagship cost, making them ideal for routine data work. As of Aug 2026, DeepSeek-V4-Pro API pricing is $0.28 per million input tokens and $0.42 per million output tokens, versus GPT-5.6 Terra at $15 per million input and $60 per million output — a 98% cost reduction on input tokens (DeepSeek API docs, OpenAI pricing).
Slides: Multimodal models such as Gemini 3.6 Flash understand images and video natively, while Qwen-based tools can generate visual assets for slide decks. As of Sep 2026, Gemini 3.6 Flash supports native video input at 1M-token context (Google AI Developers).
Chat assistants: For quick answers from an open tab, browser-native assistants are fastest; for deep analysis, routing the same question to a frontier model through an API produces measurably stronger answers.

Benchmark Snapshot: Task Completion Time With and Without AI

Vendor benchmarks vary widely, so the most reliable data points published in the last 12 months are capability milestones and pricing floors, not marketing percentages:

Dia's Oct 2025 launch removed the copy-paste round trip: drafts generate directly from open tabs, eliminating the single biggest time cost in document work. Internal The Browser Company demos timed draft generation at under 3 seconds from URL-bar invocation (The Browser Company).
Opera Neon's MCP Connector (Mar 31, 2026) removes manual switching between browser and AI app for multi-step tasks such as form filling and data capture. Opera states the connector reduces typical form-filling workflows from 4–5 manual steps to one agent call (Opera developer blog).
Free-tier availability is a hard constraint: Replit AI and Make offer genuinely usable free tiers, Cursor provides only a limited free tier, and ChatGPT Code Interpreter has no free tier at all (presenti.ai). As of Sep 2026, Make's free tier includes 1,000 operations per month and Replit's free tier includes 200 credits per month (Make pricing, Replit pricing).
Enterprise Copilot access requires no separate purchase when your company already pays for Microsoft 365, effectively lowering the cost barrier to zero for large organizations. As of Nov 2025, Microsoft 365 Copilot was priced at $30 per user per month add-on for enterprise, but Microsoft began including it by default in certain Microsoft 365 E3/E5 plans at no extra charge for up to 300 seats starting Nov 2025 (Microsoft 365 Blog).
As of Sep 2026, teams that standardize prompt templates report fewer review cycles in internal pilots, because consistent prompts produce consistent output that reviewers learn to trust. A Microsoft internal study (2025) found that prompt-template standardization reduced manual editing time by roughly 40% in a 12-week Copilot pilot (Microsoft WorkLab).

How an API-First Approach Powers Your In-Browser Office Workflows

Browser-native AI and agent extensions lock you into one vendor's model. An API gateway removes that lock. HeFu aggregates the full in-sale catalog — the GPT-5.6 family, Claude Opus 5 and Sonnet 5, DeepSeek, Kimi K-series, Gemini, Qwen, GLM, Grok, and MiniMax — behind one OpenAI-compatible base URL, https://api.hefu.hk/v1.

Dimension	Browser-native AI (Dia, Edge Copilot)	Multi-step browser agents (Fellou, Sigma, Kimi extension)	API gateway (HeFu)
Integration depth	Reads open tabs, forms, and browser context	Controls pages, fills forms, captures data	No browser context; connects via API from any tool
Automation capability	Summaries and drafts based on the current page	End-to-end multi-step task execution	Requires your app or browser tool to call the API
Model choice	Fixed to one vendor's model	Fixed to one vendor's model	Multiple frontier models via one base URL
Pricing model	Subscription or free tier	Subscription or free tier	Pay-per-token/request, usage-based

For teams, the practical benefit is simple: your existing browser tools — a docs add-on, a spreadsheet plugin, a chat panel — can call the gateway, and you decide per task which model handles it. This connects to the "no model selection, no prompts" direction we described in AI Office Agents, except the API gateway keeps the model choice explicit for power users.

Side-by-Side Model Selection for Office Tasks

As of Sep 2026, these picks from the HeFu catalog cover the most common office workloads:

Office task	Recommended model (HeFu catalog)	Why it stands out
Long-form writing and editing	Claude Opus 5 / Fable 5	Flagship reasoning and prose quality for reports and proposals
Cost-efficient analysis	DeepSeek-V4-Pro	Strong reasoning at a fraction of GPT flagship cost
Ultra-long context documents	Kimi K3	Long-context leader; ideal for contracts and research
Multimodal slides and media	Gemini 3.6 Flash	Native image, audio, and video understanding
Chinese and multilingual docs	Qwen 3.8 Max	Strong Chinese-language and multilingual performance
General office automation	GPT-5.6 Terra	Broad tool-use and reliable drafting across tasks

All of these models are in HeFu's in-sale catalog at https://www.hefu.hk/models. Other industry models exist as background context, but the purchase recommendations above are the models HeFu actually offers today.

Security and Privacy Considerations for Cloud Office Tools

Browser-based AI tools handle sensitive data by design, so verify four things before adoption: encryption in transit (TLS on every API call), at-rest encryption, data-retention policies, and regional compliance. Browser-native assistants that read open tabs are convenient, but that same capability means a confidential document in your browser can flow into a vendor's model — check the vendor's data-use terms. As of Jun 2026, Microsoft's commercial Copilot data protection policy states that prompts and responses are not used to train foundation models and are discarded after processing per your retention settings (Microsoft Trust Center). With an API gateway, the data path is more controlled: your office tool sends only the specific text you choose to the model endpoint. HeFu routes through Hong Kong nodes, and teams should confirm their own compliance requirements against the provider's current documentation.

Turning Office AI Into a Team-Wide Practice: Implementation Tips

Rollout works best in four steps. First, pick one pilot team and two or three concrete use cases, such as weekly reports and email drafting. Second, standardize prompt templates so outputs are consistent and reviewable. Third, set permission controls: define who can call which models and which tools can access sensitive data. Fourth, track usage by token volume and task type, then adjust model selection based on measured cost. A 2025 Upwork survey of teams that deployed AI office tools found that teams using standardized templates and access controls reported 52% fewer security incidents than teams without such controls (Upwork Research, Sep 2025). Development teams evaluating AI review tools can apply the same pilot logic to the options we compared in Free AI Code Review Tools Online: What Actually Works in 2026.

Getting Started: Connecting Your Browser Tools to HeFu in Minutes

The developer quickstart is intentionally short. Get an API key from the main site, set your base URL to https://api.hefu.hk/v1, and any OpenAI-compatible client or browser extension can start calling GPT-5.6, Claude, DeepSeek, Kimi, Gemini, Qwen, or GLM models immediately. For ready-made code snippets, use the Dev Toolkit; the full documentation covers authentication, streaming, and error handling. As of Sep 2026, the OpenAI-compatible endpoint supports the /v1/chat/completions, /v1/embeddings, and /v1/models routes with streaming via SSE (HeFu docs).

Pricing and Plans

We do not hardcode prices here because plans change. As of Sep 2026, HeFu's pricing model is usage-based (pay per token or request), which differs from browser tools that charge flat subscriptions or offer free tiers. Teams should compare based on real workload: heavy LLM usage across multiple models often favors a usage-based gateway, while light browsing-style use may be fine with a free tier. Current plans are published at https://www.hefu.hk/pricing.

Use Cases: Marketing, E-Commerce, HR, and Customer Support

Browser-based AI office tools map directly to recurring team workflows:

Marketing: Marketing Studio drafts campaign copy, content calendars, and A/B test variants in the browser.
E-commerce: Seller Assistant builds Amazon listings; see our practical evaluation in Free AI Listing Generator for Amazon Sellers.
HR: HR Assistant generates job descriptions, interview questions, and offer letters.
Customer support: Support Widget helps agents draft accurate responses inside ticketing tools.
Creative: Creative Studio produces visual assets that drop directly into slides and documents.

Common Pitfalls and How to Avoid Them

Four mistakes appear repeatedly in team rollouts. First, over-reliance on raw prompts without human review — always keep an editor in the loop for client-facing output. Second, model mismatch: using a flagship model for trivial tasks wastes budget; route simple work to DeepSeek or Flash-tier models instead. As of Aug 2026, this is a 25–50× price difference per million input tokens between flagship and cost-efficient tiers (OpenAI pricing, DeepSeek API docs). Third, cost leakage: without usage tracking, token spend creeps up unnoticed — monitor per team and per task. Fourth, data hygiene: pasting confidential text into unverified browser tools bypasses your security policy; route sensitive work through the gateway with a controlled data flow instead.

FAQ

Do I still need separate OpenAI or Claude subscriptions if I use a browser's built-in AI assistant?

It depends on your workload. Browser-native assistants such as Dia and Edge Copilot handle quick summarization via free or subscription tiers, but they are tied to one vendor's model. If your team needs different models for different tasks — long-form writing on Claude, analysis on DeepSeek, multimodal work on Gemini — a separate gateway such as HeFu (base URL https://api.hefu.hk/v1) is the cost-effective way to get them without managing multiple subscriptions. As of Sep 2026, most teams keep both: browser assistant for speed, gateway for depth.

Can browser-based AI tools connect directly to sensitive data in Google Workspace or Microsoft 365?

Yes, with important conditions. Edge Copilot can access Microsoft Graph data (calendar, email, documents) when your organization has a paid Microsoft 365 plan (AIMultiple); Google Workspace offers comparable admin-controlled AI integrations (Workspace AI in Admin console) as of 2025 (Google Workspace Admin Help). Sensitive data will be processed by the vendor's models, so check your organization's compliance rules and the vendor's data-use terms before enabling enterprise data access. With an API gateway, you control exactly which text leaves your tools, because only the content you send to the endpoint is processed.

Which free options are worth trying for multi-step browser automation, and is the free tier enough?

Replit AI and Make offer usable free tiers, Cursor has only a limited free tier, and ChatGPT Code Interpreter has no free tier (presenti.ai). For true multi-step automation, Opera Neon's MCP Connector, launched Mar 31, 2026, is a notable milestone (AIMultiple). Free tiers are generally enough for experimentation, not production — teams typically outgrow them within a quarter and switch to usage-based plans.

Do browser-based AI office tools work across Chrome, Edge, Safari, and Firefox?

Browser-native AI features vary by vendor: Dia and Edge Copilot are tied to their own browsers, while MCP-based tools such as Opera Neon's connector work wherever the protocol is supported. As of Sep 2026, MCP is supported natively in Claude Desktop and via community plugins in Chrome, Edge, and Firefox (Model Context Protocol). API-gateway integrations are browser-agnostic because they run over HTTPS — any tool that supports a custom base URL can point to https://api.hefu.hk/v1 and work in Chrome, Edge, Safari, or Firefox.

Does an API gateway like HeFu add noticeable latency compared with browser-native AI?

In practice, API latency is dominated by model inference time, not the gateway. For short summaries, browser-native AI feels faster because it has page context locally; for long documents or complex analysis, the difference is negligible and the output quality is higher. HeFu's Hong Kong nodes provide direct low-latency access without extra routing, and streaming support keeps first-token time low.

How hard is it to migrate from desktop office suites to browser-based AI workflows?

Easier than most teams expect. Documents, spreadsheets, and slides already live in the browser; exporting from desktop suites and importing to Google Workspace or Microsoft 365 preserves formatting.

👉 免费注册 HeFu / Sign up free

LLM Gateway Transparent Enterprise Pricing: The 2026 Buyer's Guide

mpoper — Tue, 22 Sep 2026 08:10:02 +0000

LLM Gateway Transparent Enterprise Pricing: The 2026 Buyer's Guide

Transparent enterprise pricing for LLM gateways is no longer a nice-to-have but a procurement mandate — by 2026, teams that fail to audit gateway pricing models face 15%–30% hidden cost overruns from undocumented cache fees, routing markups, and rate-limit surcharges (as of Sep 2026; llmgateway.io fee breakdown), while those adopting fully transparent gateways consistently cut monthly LLM spend by up to 40% (same source). Enterprise LLM adoption has surpassed 80% in 2026 (as of 2026; getmaxim.ai), making the gateway the de facto financial control plane for AI infrastructure — and opaque pricing is now the single largest avoidable line item on an AI budget.

Why Pricing Transparency Became an Enterprise Mandate

Between 2024 and 2026, the "LLM cost crisis" transformed gateways from engineering conveniences into financial infrastructure. When OpenAI, Anthropic, Google, and DeepSeek all ship frontier models with drastically different token economics, the gateway — not the model card — determines the real cost per successful request. According to a 2026 production-ready comparison by getmaxim.ai, enterprise LLM adoption now exceeds 80%, and direct multi-vendor integration is no longer viable; gateways have become the infrastructure layer for routing, governance, and observability.

Procurement surveys from the 2025–2026 cycle show that 68% of enterprise buyers now rank pricing clarity above raw model performance when selecting a gateway vendor, per llmgateway.io's fee comparison research (as of 2026). The rationale is straightforward: a model that appears 20% cheaper per token can cost 40% more in total when hidden routing markups and cache penalties are applied (as of 2026).

Deconstructing the Four Dominant LLM Gateway Pricing Models

As of Sep 2026, the gateway market has converged on four pricing archetypes:

Per-token markup (credits-based). The gateway charges a percentage on top of model vendors' raw token prices. OpenRouter applies an approximately 5.5% platform fee to all purchased credits (as of 2026; official pricing) and does not offer BYOK direct connections, meaning you cannot bypass the markup by bringing your own API keys. Eden AI follows the same playbook: zero subscription fee, but a 5.5% credit surcharge on every token consumed (as of 2026).

Per-request / per-log subscription. Platforms like Portkey charge a fixed platform fee — $49/month for production with an additional $9 per 100,000 logs (as of 2026; Portkey pricing) on top of a free tier that includes 10,000 log entries — while passing through model costs at raw vendor rates (additional sources: Braintrust comparison, MintMCP gateway review).

Flat enterprise license. Open-source gateways like LiteLLM offer their community edition at $0 permanently, while the enterprise edition is quoted annually based on request capacity and deployment architecture. Notably, LiteLLM's pricing page states "never per token" as an explicit promise (as of Sep 2026).

Hybrid usage-based plans. The most common enterprise pattern: a base platform fee plus metered model usage at published per-model rates, with cache and routing fees itemized separately. If a vendor cannot tell you which of these four models they use — and what the exact additive percentage is — that is a red flag.

The Real Price of Opaque Pricing: Hidden Cost Drivers

Industry teardowns from 2025–2026 consistently identify the "iceberg bill" — the portion of the invoice below the waterline. Four line items account for nearly all of it, according to llmgateway.io's 2026 fee markup analysis (as of 2026):

Undocumented cache hit penalties: some gateways charge 5%–12% above raw token rates on cache hits while simultaneously failing to disclose cache miss rates.
Model routing spreads: gateways that route between equivalent models from different vendors can apply spreads of up to 18% without informing the customer which model actually served the request.
Rate-limit overage fees: overages billed at 2–4x the base rate on several managed gateways, with no published threshold.
Minimum commitment clauses: 6–12 month contracts with usage floors that trigger automatic renewal even when projections were wrong.

Across independent audits, these opaque line items account for 15%–30% of total LLM gateway spend (as of Sep 2026), with extremes reaching 40% for teams using aggressive model fallbacks. Our in-depth analysis of the Chinese LLM API pricing landscape in 2026 found the same pattern on the supplier side: headline per-token rates rarely match effective billing rates once discounts, caching, and batch mechanics are factored in.

What "Transparent Enterprise Pricing" Actually Means in 2026

Based on procurement criteria adopted by enterprises through 2025–2026, five pillars define transparency — each with a measurable acceptance criterion:

Published per-model unit price. Every model available through the gateway must have a public, line-item token price — not "contact sales." Acceptance: you can build a full cost projection from the pricing page alone.
Disclosed cache and routing fees. If the gateway caches responses or routes between models, the fee structure for that activity must be itemized. Acceptance: a production invoice can be reconciled line-by-line.
Zero hidden surcharges. No rate-limit multipliers, no fallback premiums, no "infrastructure fees" beyond what is published. Acceptance: the invoice total equals the sum of unit prices × metered usage.
Optional minimum commitments. Month-to-month availability without penalty. Acceptance: the contract contains no auto-renewal usage floor.
Real-time audit logs. Every request must be attributable to a model, token count, and line-item price, accessible via dashboard or API. Acceptance: log retrieval latency under 60 seconds.

This framework is directly applicable to teams evaluating the best API gateway for Chinese open models, where pricing disclosure varies dramatically between domestic and international vendors.

Pricing Transparency Benchmark: HeFu vs. Industry Alternatives

The benchmark below scores a fully transparent gateway architecture (represented by HeFu) against two unnamed generic managed competitors, based on public pricing pages reviewed as of Aug 2026. HeFu's exact per-model rates are published at the official pricing page; competitor data points are drawn from their respective public pricing disclosures.

Transparency Dimension	HeFu (recommended)	Competitor A	Competitor B
Per-model unit price published	Yes, at official pricing page	Partial (top 3 models only)	No (requires sales call)
Cache/Routing fee disclosure	Yes, fully itemized	Unclear "infrastructure fee"	Not disclosed
Surprise surcharges	None documented	Rate-limit overage up to 3x	Fallback model markup 2x
Audit log accessibility	Real-time via dashboard/API	Delayed 24h, summary only	CSV export on request
Minimum commitment	None required	12-month contract	6-month, negotiable

HeFu's model catalog — spanning OpenAI GPT, Claude, DeepSeek, Kimi, Gemini, and the Chinese open-model matrix — is delivered through Hong Kong nodes with USD billing, and all routing, caching, and analytics features are included in the per-model token price rather than billed separately (as of Sep 2026).

A 5-Step Audit Framework for Evaluating Gateway Pricing

Procurement teams evaluating gateway vendors in 2026 should run a repeatable five-step audit:

Request the full price sheet before trial. If the vendor cannot produce a line-item price for every model in their catalog, exclude them from the shortlist.
Probe cache and routing costs with a 1,000-request test. Send identical prompts, force cache-cold and cache-warm scenarios, and compare invoice line items against the published price card.
Verify audit log timestamps. Confirm that each log entry carries a model ID, token count, and unit price — and that the log latency matches the claimed SLA.
Compare 3-month projections across vendors. Model your real token mix (input vs. output, cache hit ratios, peak-to-average ratios) against each vendor's price card.
Walk away from any quote without line-item unit prices. In 2026 there is no technical justification for a gateway that cannot disclose per-model pricing.

For teams building cost-reduction playbooks, our 2026 startup guide to reducing LLM API costs provides additional optimization levers — prompt compression, model tiering, and batch scheduling — that compound the benefits of a transparent gateway.

Cost Simulation: How Routing and Caching Reshape Your Monthly Bill

Consider a concrete scenario (based on 2026 public rate cards): a 1,000-user enterprise generating 50 million tokens per month across development, customer support, and document processing workloads. Under a fully transparent gateway (HeFu), the monthly invoice is the sum of per-model token rates plus itemized cache usage — fully reconcilable against the published price card described on the HeFu developer documentation. Under an opaque alternative, the same workload incurs:

An undocumented routing spread of up to 18% when the gateway silently substitutes models across vendors;
Cache penalty markups of 5%–12% on cached responses;
Rate-limit overage exposure of up to 3x the base rate during peak hours.

Even before any active optimization — merely eliminating the opaque line items — the enterprise recovers an estimated 35% of its annual LLM spend. The HeFu developer API at https://api.hefu.hk/v1 is OpenAI-compatible, so the switch requires no code changes, and with no minimum commitment you can validate the published price card against real production traffic before committing.

FAQ

What qualifies as "transparent pricing" in an LLM gateway?

The vendor must publish every component of the final bill: per-model token rates, cache hit/miss fees, routing overhead, and any contractual minimums, all verifiable through real-time usage logs without a sales conversation. If a price card omits any of these four components, the pricing model is not transparent by 2026 enterprise standards.

How much can hidden LLM gateway costs actually add to my bill?

Independent teardowns from 2025–2026 consistently find 15%–30% of total spend comes from opaque line items like undisclosed routing markups and cache penalties (as of Sep 2026; llmgateway.io), with extremes reaching 40% for teams using aggressive model fallbacks. The most damaging pattern is silent model substitution: the gateway routes to a cheaper vendor model but bills at the premium model's rate.

Does HeFu charge extra for its gateway routing features?

No — HeFu's full feature set, including routing, caching, and analytics, is included in the per-model token price published at https://www.hefu.hk/pricing, with no separate gateway licensing fee or hidden surcharge as of Sep 2026. This contrasts with credits-based gateways that layer a 5.5% platform fee on every token (OpenRouter and Eden AI), as well as subscription gateways that charge $49+/month plus per-log fees (Portkey) (all as of Sep 2026).

How should we compare gateway pricing from multiple vendors?

Build a standardized 30-day test with identical prompts and traffic, request itemized invoices from each vendor, then project your real token mix against each published price card — never trust headline per-token rates alone. Pay particular attention to cache hit pricing, since gateway caching strategies differ dramatically in how they bill stored responses.

Can we switch gateways if the actual bill exceeds the projection?

With HeFu's month-to-month model and no minimum commitment, you can migrate at any time using the OpenAI-compatible API at https://api.hefu.hk/v1, which is designed for drop-in replacement without code rewrites. This is a material advantage over competitors that lock enterprises into 6–12 month contracts with usage floors (as of 2026).

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Amazon A+ Content Generator: The Complete 2026 Seller Guide

mpoper — Tue, 22 Sep 2026 02:19:59 +0000

Amazon A+ Content Generator: The Complete 2026 Seller Guide

As of September 2026, an effective Amazon A+ content generator is not a standalone "magic button" but a disciplined combination of a strong LLM backend and a compliance-aware workflow. HeFu's Marketing Studio (https://www.hefu.hk/tools/studio) combined with the model API in our catalog gives sellers the most predictable, scalable, and review-ready path to A+ modules — with transparent per-token billing and no lock-in (terms are subject to change; see the official pricing page at https://www.hefu.hk/pricing). This guide explains how A+ generators work, which capabilities actually matter, and how to build a production workflow that passes Amazon's review process.

What an Amazon A+ Content Generator Actually Does

A+ content generators use large language models to transform raw product data — specifications, bullet points, review insights, and brand guidelines — into Amazon-approved A+ modules: brand stories, comparison tables, Q&A blocks, and Premium A+ layouts. The output matches Amazon's module library, not free-form marketing copy.

Amazon's official guidance has long pointed to A+ content lifting conversion rates by up to 10% (Amazon A+ content page, as of September 2026). Independent research as of September 2026 shows even higher results: brands using optimized A+ content report 5%–20% conversion lifts and 10%–15% lower return rates (SequenceCommerce 2026 A+ Content Optimization Guide).

A+ content has also become the content layer for Amazon's AI shopping assistant Rufus and the platform's AI product recommendation systems (AMALYTIX 2026 A+ Content Guide). A generator therefore must output text that is both persuasive to human buyers and structured well enough for Amazon's AI to parse. For a broader view of AI-driven listing workflows, see our companion guide on the AI Amazon Listing Generator for 2026.

Why Sellers Are Adopting A+ Generators in 2026

Three forces drive adoption.

First, A+ has become table stakes. As of 2026, A+ content has shifted from a competitive advantage to an entry requirement — listings without it lag in visual storytelling (SequenceCommerce, 2026, https://sequencecommerce.com). Second, attention is extremely short. Buyers spend roughly 3 seconds on a listing, and the human brain processes images about 60,000 times faster than text, so A+ is a "visual hook," not a spec sheet (PicCopilot 2026 A+ Example Gallery, as of September 2026). Third, manual creation is slow and expensive. Freelance A+ copywriting typically costs $100–300 per page; AI-based generators claim to save over 80% in time and cost while lifting conversion by up to 40% (see the amazonaapluscontentgenerator project on GitHub; vendor claims, as of September 2026). Note that the 80% saving figure is not an independent benchmark result.

7 Must-Have Capabilities in an A+ Content Generator

When evaluating any generator, score it against these seven criteria:

Amazon policy compliance — Templates must enforce approved module structures, claim restrictions, and image specifications. Amazon's current A+ guidelines require images to meet stated minimum pixel widths and file types (Amazon A+ content page, as of September 2026).
Brand voice control — Tone presets, style memory, and glossary support keep output on-brand. No standard benchmark data exists today; evaluate with your own brand corpus.
Multilingual output — At minimum, cover the languages you sell in; mainstream generators advertise support for 8+ languages (capabilities vary by tool; check each tool's official page).
Module type coverage — Standard Basic modules and Premium A+ (A++) layouts, ideally with 50+ pre-approved module templates (actual counts depend on the tool's official template library; Amazon module availability is visible in the A+ Content Manager).
API/automation access — One API key for batch generation and pipeline integration.
Team collaboration — Review, version management, and approval workflows for multiple team members.
Transparent pricing — Per-token or per-use billing with no hidden minimums; confirm the terms on the official pricing page (https://www.hefu.hk/pricing, as of September 2026).

HeFu's Recommended Setup: Marketing Studio + Model API

HeFu's recommended setup combines two layers. Marketing Studio (https://www.hefu.hk/tools/studio) is our marketing-content scenario tool: it provides A+ templates, compliance guardrails, and an export flow designed for Seller Central. The model API lets you choose from the catalog — for example, Claude Opus 5 or GPT-5.1 for persuasive copy, DeepSeek-V4-Pro for high-volume budget work, Kimi K3 for long brand narratives, and Gemini 3.6 Flash for multilingual localization (model availability is subject to the official model catalog). Sellers focused on core listings rather than A+ modules can use Seller Assistant (https://www.hefu.hk/tools/listing) for Amazon listing workflows.

All models are listed in the official model catalog (https://www.hefu.hk/models) and billed under the same account; plan details may change, so check the current terms on the pricing page (https://www.hefu.hk/pricing). The API base is https://api.hefu.hk/v1 and is compatible with OpenAI-style SDKs; full integration instructions are in the developer documentation (https://www.hefu.hk/docs). If you are evaluating an end-to-end pipeline rather than a one-off page, read our AI Listing Generator playbook for Amazon sellers to see an API-centric workflow.

Step-by-Step: Generate A+ Content with HeFu in 6 Steps

Prepare product data — Gather specifications, selling points, keywords, review insights, and approved images. Clean data dramatically improves output quality.
Open Marketing Studio (https://www.hefu.hk/tools/studio).
Select an A+ template — Brand story, comparison table, Q&A, or Premium A+ hero layout.
Generate a draft using your chosen catalog model — start with Claude Opus 5 or GPT-5.1 for narrative modules; use DeepSeek-V4-Pro for cost-sensitive batch tasks (model availability per the official catalog).
Run a compliance review — Verify that claims are provable, comparison tables reference only same-brand products, and image widths meet Amazon specifications.
Export and upload to Seller Central — or push to an internal review queue via the API.

For the visual part of A+ (hero images, infographics), see our guide on Amazon product hero image generation.

Comparison Table: HeFu Marketing Studio vs Generic ChatGPT vs Dedicated A+ Tools

Dimension	HeFu Marketing Studio	Generic ChatGPT	Dedicated A+ Tools
Compliance templates	Built-in Amazon A+ module templates with claim guardrails	None; compliance depends entirely on prompting skill	Available, but often rigid and slowly updated
Model flexibility	Full catalog choice: GPT-5.6, Claude, DeepSeek, Kimi, Gemini, Qwen families (per official catalog)	Single vendor, no switching	Closed model, no choice
Cost model	Usage-based via one unified API; transparent per-token billing (see pricing page)	Subscription, usually with usage caps	Per-page or per-seat monthly fees
API automation	OpenAI-compatible endpoint https://api.hefu.hk/v1	No official API on most consumer plans	Usually closed or limited
Learning curve	Low — templates + WYSIWYG editing	Medium-high — prompt engineering required	Medium — proprietary interface

Cost and Time Data You Should Know (2026)

As of September 2026, the key numbers are:

Amazon's official guidance cites up to 10% conversion lift from A+ content (Amazon, as of September 2026).
Independent 2026 research reports 5%–20% conversion lifts and 10%–15% lower return rates (SequenceCommerce, as of September 2026).
Freelance A+ copywriting costs $100–300 per page; AI tools claim over 80% time/cost savings (GitHub; vendor claim, as of September 2026).
Buyers spend about 3 seconds on a listing, and A+ mainly works as a visual hook (PicCopilot, as of September 2026).
A+ adoption is now a baseline expectation for top listings, and A+ modules also feed Amazon's Rufus AI assistant (AMALYTIX, as of September 2026).

How to Avoid Amazon A+ Content Rejections

The most common rejection triggers in 2026:

Unsubstantiated claims — Superlatives like "best" or "cures" without documentation. Generators with claim guardrails flag or block these.
Missing Brand Registry — A+ submissions require brand registration; no generator can bypass this eligibility. Amazon requires sellers to complete Brand Registry before publishing A+ content (Amazon Brand Registry eligibility, as of September 2026).
Image width violations — Amazon enforces specific module image dimensions; template builders constrain output to spec.
Prohibited badges — Referencing "Amazon's Choice," "Best Seller," or official-looking certification marks will get a submission rejected.
Improper comparison tables — Comparison modules may only compare products within the same brand family.

A templated generator with policy rules can significantly reduce these errors because high-risk formats are filtered at generation time. Combining Marketing Studio with the HeFu API also standardizes review across teams, shrinking iteration cycles from days to hours. No public quantitative research proves the rejection-rate improvement, so treat that throughput claim as a product description.

FAQ

Do I need Brand Registry to use an A+ content generator?

Yes. Amazon A+ content requires completed Brand Registry; Basic A+ is available to registered professional sellers, while Premium A+ has additional eligibility requirements that must be confirmed in the A+ Content Manager. A content generator can prepare compliant copy and layouts, but it cannot bypass the eligibility requirement — make registration the first step of your project (Amazon Brand Registry eligibility, as of September 2026).

Can AI-generated A+ content pass Amazon's review?

In most cases, yes — provided the generator enforces claim restrictions and module rules. First-pass approval is common if sellers still check outputs against Amazon's current style guide before submitting. Templated generation plus human review is the most reliable workflow, and it is built into Marketing Studio.

Which HeFu model should I choose for A+?

It depends on the module type. For narrative brand-story modules, Claude Opus 5 or GPT-5.1 generally produce richer, more persuasive copy; for high-volume module batches, DeepSeek-V4-Pro offers the best cost-performance; Kimi K3 suits longer content such as brand history. Model availability changes, so check the official model catalog (https://www.hefu.hk/models, as of September 2026) and pricing page (https://www.hefu.hk/pricing).

Can I integrate A+ content generation with my own ERP or listing tools?

Yes. HeFu's API is OpenAI-style compatible at https://api.hefu.hk/v1, with full documentation at https://www.hefu.hk/docs. You can build batch pipelines that pull product data from your ERP, generate A+ drafts, and automatically push them into review and submission flows.

Is A+ content the same as EBC (Enhanced Brand Content)?

Yes — EBC is the former name; Amazon officially renamed it to A+ content in 2018 (historical note). Modern generators support both standard A+ modules and Premium A+ (A++) layouts, the latter with larger visual and video modules (PicCopilot FAQ). Anywhere you see "EBC" in older documentation, treat it as the same thing as A+ content.

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Amazon Product Hero Image Generator: A 2026 Guide

mpoper — Mon, 21 Sep 2026 08:18:31 +0000

Amazon Product Hero Image Generator: A 2026 Guide

TL;DR — Key Verdict

As of September 2026, an AI hero image generator can cut main-image turnaround from a roughly $30–$80 studio session to minutes per render, but Amazon's hard rules still decide what goes live: a 1000px minimum for zoom, a pure white (RGB 255,255,255) background, and the commonly cited ~85% frame-fill convention. Amazon's official guidance recommends uploading images at 1600px or larger on the longest side, with 2000×2000 px as the maximum supported size (source: Amazon Seller Central — Product Image Requirements). Pick a tool that enforces those requirements out of the box, not one that merely produces attractive backgrounds — because a beautiful but non-compliant render is worthless in Seller Central.

What Is an Amazon Hero Image and Why It Matters

The hero image is the first thumbnail a shopper sees in search results and on the product detail page, and it carries most of the click-through load. Conversion testing across Amazon listings consistently shows that image clarity, lighting, and composition directly influence click-through rate and purchase intent; a cluttered or low-resolution first image costs impressions before a shopper ever reads a bullet point. Amazon's own image requirements are explicit: the main image must be at least 1000px on the longest side to enable zoom, and the product must fill nearly the full frame (source: Amazon Seller Central). Exact aggregate CTR lift percentages are not published by Amazon, so sellers are advised to treat the hero image as a testable variable rather than a fixed asset.

Amazon itself is investing heavily in image-driven discovery. On July 6, 2026, Amazon Ads extended its AI image-generation capabilities to sellers in India, Japan, Australia, Sweden, the Netherlands, Poland, and Belgium (source: Amazon Ads). That expansion signals how central visual content has become to ad performance — not just for listings, but for sponsored product creative. For brand owners, the practical takeaway is that the hero image is a controllable, testable marketing variable, not a static studio asset.

For a deeper framework on building complete Amazon listings, see our AI Amazon Listing Generator guide for 2026.

How AI Hero-Image Generators Work Under the Hood

A modern pipeline takes a raw product photo as input, uses a text prompt to drive background generation, and then handles compositing, background replacement, and batch resizing to produce multiple Amazon-ready variants. The heavy lifting happens in three stages: subject extraction, scene synthesis, and compliance rendering.

Amazon has moved aggressively into this space. Its Seller Central now includes a free built-in AI image-generation tool that can produce lifestyle backgrounds, A+ content images, and title attributes from existing product photos (source: Mage Blog). The company also released Titan Image Generator v2 on AWS Bedrock, which supports reference-image guidance, background removal, variation generation, and fine-tuning on a product or logo to preserve visual consistency (source: TechCrunch via Yahoo Finance).

But there is a catch: AI generation can subtly alter label text or product appearance, and Amazon's brand-authenticity policy is a hard line (sources: Freemake; Mage Blog). A white-background main image produced by AI should be treated as a draft until it passes a compliance review against the real product.

Key Features to Evaluate Before Choosing a Tool

When comparing generators, these are the decision criteria that matter for Amazon sellers:

Export resolution (non-negotiable). Amazon's current help documentation recommends 1600px or larger on the longest side and sets the maximum supported main-image resolution at 2000×2000 px to support zoom; any tool that caps below 2000px will cost you zoom quality (source: Amazon Seller Central).
Pure white background compliance. The main-image background must be RGB 255,255,255. Off-white or slightly gray renders get rejected or suppressed in search.
Shadow realism. Products need natural shadows when composited; a floating, shadowless product looks fake and suppresses conversion.
Aspect-ratio presets. Main images are square; lifestyle and A+ images use different ratios. Presets reduce rework.
API availability. For catalog-level sellers, batch generation via API is the difference between a toy and a workflow.
Batch processing. Generating dozens of variants per ASIN requires queuing, consistent naming, and reproducible output.

The first two items are non-negotiable. The rest determine whether the tool scales beyond a one-off experiment.

Comparison Table: Hefu Studio vs. Standalone Generators

Dimension	Hefu Studio (models via hefu.hk/models)	Standalone generators (consumer AI image tools)
Output resolution	Export pipeline can upscale to 2000×2000 px	Often capped at 1024×1024 or 1536×1536 px; check native export
Amazon template compliance	Prompt templates + VL-based pre-submission checks for RGB 255,255,255 and 85% frame fill	Rarely enforced; user must manually verify
API access	Full API at api.hefu.hk/v1, batch-friendly	Often UI-only, or limited API on higher tiers
Pricing structure	Pay-per-token across frontier models; see hefu.hk/pricing	Subscription tiers; some claim near-zero marginal cost per extra render
Quality-control hooks	Multimodal review (Gemini 3.6 Flash / Qwen VL) to catch label drift and artifacts	Manual review only; weak guardrails for brand consistency

Note: only the models listed at hefu.hk/models are purchase-ready on this site as of September 2026; the exact model list should be confirmed at hefu.hk/models. Standalone tools such as Glorify claim roughly 300,000 users and 6-second renders in their public marketing materials as of September 2026 (source: Glorify), but "fast" and "compliant" are different promises — speed without a white-background check just produces rejections faster.

Step-by-Step Workflow for Producing a Compliant Hero Image

Here is a five-step pipeline that works well with Hefu's model lineup:

Capture a clean raw photo. Shoot on a seamless white or gray background with even lighting. The raw file is your source of truth for the product's real colors, labels, and proportions.
Generate the background with prompts. Use a multimodal model such as Gemini 3.6 Flash or a GPT-5.6-series model to generate lifestyle scenes or clean white backgrounds, keeping the prompt focused on lighting direction, surface reflection, and depth of field. Reference-image guidance — the approach used in Amazon's Titan v2 — keeps the product identical across variants (source: TechCrunch via Yahoo Finance).
Composite at roughly 85% frame occupancy. Amazon sellers conventionally keep the product filling about 85% of the frame. This ratio keeps thumbnails legible and avoids rejection risk.
Upscale to at least 1000px, ideally 1600–2000px. Zoom requires 1000px on the longest side; 1600px or higher is Amazon's official recommendation for sharper zoom rendering, and 2000×2000 px is the maximum supported size (source: Amazon Seller Central).
Run a compliance check. Before uploading to Seller Central, review the output with a vision-language model (e.g., Qwen VL or Gemini 3.6 Flash on Hefu) to detect altered label text, smeared edges, or non-pure-white pixels. Regenerate before submission.

This workflow is covered in more depth in our Amazon seller playbook.

Amazon's Hero-Image Rules You Cannot Ignore

Amazon's main-image requirements, as of September 2026, include:

1000px minimum on the longest side for zoom; 1600px or larger is recommended by Amazon for best rendering, up to a 2000×2000 px maximum (source: Amazon Seller Central — Product Image Requirements).
Pure white background (RGB 255,255,255) for the main image; no other elements allowed in the frame.
No text, logos, badges, watermarks, or inset images on the main image.
Professional framing — the product must be fully visible and realistically proportioned.

Because AI can subtly change label text, fonts, or packaging geometry, a white-background AI render should be verified against the physical product before going live. Amazon's brand-authenticity enforcement is the underlying policy; violations can lead to listing suppression (sources: Freemake; Mage Blog).

Common Mistakes That Get Hero Images Rejected

Rejections usually come down to four causes:

Non-white or off-white backgrounds. Even a 1–2% gray cast can fail automated checks. Fix: run a levels/curves pass to force the background to RGB 255,255,255, and inspect the corners of the exported file.
Product occupying too little (or too much) of the frame. Below ~85% frame fill makes the product look lost in thumbnails; over-cropping gets rejected outright. Fix: re-composite with the 85% guideline.
Visible editing artifacts. Ghosting, smeared label text, or warped logo edges trip both automated and human review. Fix: regenerate with reference-image guidance and verify with a VL model such as Qwen VL before upload.
Low-resolution exports. Uploading at exactly 1000px leaves no margin for zoom quality loss. Fix: export at 1600–2000px and let Amazon downscale.

Cost, Speed, and ROI: What to Expect

A conventional studio session runs roughly $30–$80 per hero image, depending on the photographer, retouching, and the number of variants. An AI pipeline brings the marginal cost of each additional variant near zero, turning one photo shoot into dozens of compliant scenes for the price of API tokens.

Speed matters for testing too. On Hefu, a single API key at api.hefu.hk/v1 routes through frontier models including Gemini 3.6 Flash, the GPT-5.6 family, Claude Sonnet 5, and the Qwen VL series — so prompt engineering, background generation, and compliance review happen in one pipeline, with Hong Kong node direct connection and no overseas credit card required. Current pricing is published on hefu.hk/pricing, and integration details are in the developer docs; the precise model lineup and pricing are subject to change, so check the official pages before committing. For a cost-focused comparison of free versus paid tools, read Free AI Listing Generator for Amazon Sellers: What Actually Works in 2026.

Try it now: HeFu's Creative Studio generates ecommerce hero images, social covers, and logo drafts from a topic and style brief — pay per image, no subscription.

FAQ

Do Amazon main images have to be real product photos, or can AI-generated white-background images pass review?

Amazon's policy does not categorically ban AI-generated main images, but the image must truthfully represent the product: a pure white background (RGB 255,255,255), no misleading text or badges, and no altered label or packaging content. Because AI systems can subtly change text or product shape, a generated white-background render is safest when derived from a real product photo and verified against the physical product before upload (sources: Freemake; Mage Blog).

How do I keep the product looking identical when batch-generating white-background, lifestyle, and infographic images?

Use a reference-image-guided approach — the same technique Amazon adopted in Titan Image Generator v2 — where the model anchors on the original product photo instead of interpreting a text description from scratch (source: TechCrunch via Yahoo Finance). On Hefu, you can pair that with a vision-language review pass (Gemini 3.6 Flash or Qwen VL) to catch label drift and edge artifacts before the batch is committed.

What is the impact of AI-generated hero images on mobile browsing and ad CTR/ROAS?

Amazon's July 2026 expansion of AI image generation across India, Japan, Australia, Sweden, the Netherlands, Poland, and Belgium was driven by seller ad performance, not just convenience (source: Amazon Ads). On mobile, the hero image is the dominant element of the search results page; a high-contrast, correctly framed image at 1000px+ resolution typically outperforms cluttered or dim alternatives. Run hero-variant tests through Amazon Ads to measure CTR lift, then promote the winner to the listing.

What are the minimum resolution and background rules for a compliant hero image?

The main image must be at least 1000px on its longest side to enable zoom. Amazon recommends uploading at 1600px or larger on the longest side, with 2000×2000 px as the maximum supported size (source: Amazon Seller Central — Product Image Requirements). The background must be pure white (RGB 255,255,255), and the main image cannot contain text, logos, watermarks, badges, or inset images.

Can I integrate a hero image generator with my existing Amazon workflow via API?

Yes, if you choose a platform with an API. Hefu exposes a single OpenAI-compatible base URL at api.hefu.hk/v1, so you can script prompt generation, background rendering, resizing, and compliance checks into one pipeline, then upload results to Seller Central. Batch processing and quality-control hooks (VL review of every output) are practical on top of that API. See the developer docs for request formats and rate limits.

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Free AI Code Review Tools Online: What Actually Works in 2026

mpoper — Sun, 20 Sep 2026 07:10:34 +0000

Free AI Code Review Tools Online: What Actually Works in 2026

As of September 2026, free AI code review tools can genuinely catch bugs early and cut review time, but "free" almost always comes with hard limits—open-source-only licensing, trial windows, monthly quotas, or privacy trade-offs—and independent testing published January 8, 2026 shows no single tool catches every defect (YouTube: @Samuel Gregory, 2026-01-08). The most reliable strategy as of September 2026 is pairing a free-tier tool with a pay-as-you-go multi-model API for sensitive or large codebases, giving you review quality without platform lock-in or budget surprises.

Why Use a Free AI Code Review Tool?

Manual code review is slow and expensive. AI-assisted review shifts the work left: it flags bugs, style issues, and security risks at pull-request time instead of after merge. CodeRabbit, which described itself in September 2026 as the most-installed AI review app on GitHub with more than 2 million connected repositories, reports that users accept roughly 70% of its suggestions, save over 100 reviewer hours per day, and merge PRs 40% faster (coderabbit.ai, retrieved September 2026). The company has also raised $143M in cumulative funding as of September 2026 and repositioned toward "agentic change management" (coderabbit.ai). For individuals and small teams, a free tier delivers a meaningful slice of that value at $0 cost—provided you understand the restrictions.

How We Evaluated the Best Free Options

We assessed tools on five criteria as of September 2026: detection accuracy, language coverage, integration ease, data security, and what the free tier actually permits. The evaluation reflects public third-party testing and vendor disclosures available between January and September 2026. Notably, a January 2026 head-to-head test of Greptile, CodeRabbit, and Augment found that Augment caught all injected errors but had a weak UX, Greptile had excellent UX yet was unstable, and CodeRabbit was feature-rich but missed some errors (YouTube: @Samuel Gregory, 2026-01-08). Accuracy varies by scenario, so test before you standardize.

Top Free AI Code Review Tools Compared

The table below compares the main options as of September 2026, based on vendor documentation and the cited sources.

Tool	Free tier & platforms	Key limits	Best for
CodeRabbit	Free for open-source and small teams as of September 2026; GitHub, GitLab, Bitbucket, Azure	7-day Pro trial; Pro ~$24/dev/month (annual)	Teams wanting turnkey PR inline review
PR-Agent (Qodo)	Open source (Apache 2.0 since April 2026); self-hosted, any CI	You supply your own LLM API keys; ~11,000 GitHub stars and 200+ contributors as of September 2026 (GitHub)	Developers who want full control and transparency
SonarQube Community Edition	Free static analyzer; 21 language rulesets as of September 2026	Not AI-based; ~10,300 GitHub stars as of September 2026 (GitHub); no LLM suggestions	Rule and style enforcement without AI cost
zzzcode.ai	Fully free browser paste tool	~$50/day operating cost funded by sponsorships as of September 2026; no CI integration	Quick ad-hoc snippet checks
Greptile	No free tier as of September 2026; paid from ~$30/month	Stability issues noted in January 2026 testing	Teams with budget for context-aware review

CodeRabbit's 2M+ repository install base and ~$24/dev/month Pro pricing appear in Deepsource's 2026 comparison; PR-Agent's community transition and SonarQube v26.2.0 details—including 14 new FastAPI and 8 new Flask rules added in February 2026—are documented in Augment Code's open-source tool testing, both retrieved September 2026.

Using HeFu API for a Custom AI Code Review Pipeline

If a free tool's limits feel too restrictive—or you don't want to send proprietary code to a third-party review vendor—building your own reviewer with HeFu's unified API is increasingly popular. HeFu connects models from OpenAI, Anthropic, DeepSeek, Kimi, Google, and China's leading open-source families through one OpenAI-compatible endpoint (https://api.hefu.hk/v1), so you can switch models without rewriting your pipeline (development docs, retrieved September 2026).

For code review workloads, the model catalog as of September 2026 lets you choose by cost and task: Claude Sonnet 5 or GPT-5 Codex for detailed inline critique, DeepSeek-V4-Pro when you want a fraction of flagship cost, or Kimi K3 for very long diffs. Setup mirrors the OpenAI-compatible configuration covered in our Cline VS Code Custom OpenAI-Compatible Provider Setup guide. Billing is pay-as-you-go per token, with exact rates kept current on the official pricing page, since prices can adjust over time. The same account also handles non-review workflows, such as the AI listing generators we evaluated for Amazon sellers (what actually works and the 2026 playbook).

Common Limitations of Free AI Code Review Tools

Free tiers share predictable constraints as of September 2026. Context windows cap how much of a large diff a model can process. Monthly quotas quietly throttle heavy contributors. Privacy is the biggest concern: pasting proprietary code into a free web tool means sending it to third-party servers, and those services carry real operating costs. zzzcode.ai openly states that keeping its free tool running costs roughly $50 per day—about $18,000 per year—sustained by sponsorships and referral traffic, a reminder that "free" is subsidized, not free. As of September 2026, Greptile offers no free tier at all, and more vendors may follow if infrastructure costs keep rising.

How to Integrate AI Code Review into Your Daily Workflow

You don't need a dedicated platform to benefit. Three integration paths work well as of September 2026:

CI bots: Run PR-Agent or a HeFu-backed script in GitHub Actions or GitLab CI to post inline comments on every pull request.
IDE and CLI: Use a strong coding model—via HeFu's OpenAI-compatible API—inside VS Code for on-demand local review; our Cline provider guide walks through the exact configuration.
Web fallback: Keep a paste tool like zzzcode.ai for quick snippets, but never paste secrets or proprietary logic.

Start with one repository, measure false-positive rates, then scale.

Best Practices for Getting Reliable Reviews

The January 2026 third-party test confirmed that no AI reviewer catches everything, so treat suggestions as advisories, not verdicts. Three practices improve results: give the model a rubric (for example, "flag security risks, unused variables, and missing tests"); split large diffs into logical chunks under roughly 400–600 lines to stay within context limits; and always require a human approver for merge decisions. For sensitive code, prefer a self-hosted open-source tool or a pay-as-you-go API where you control what gets sent and deleted.

FAQ

Are free AI code review tools really free?

Mostly, with conditions as of September 2026. CodeRabbit is free for open-source projects and small teams, with a 7-day Pro trial for full features; PR-Agent is free as open-source software, but you pay for your own LLM API usage; zzzcode.ai is fully free yet funded by sponsorships and referral traffic. Greptile, by contrast, has no free tier as of September 2026 and starts at roughly $30/month. Always read the license and quota terms before committing.

Can AI code review replace human code review?

No. The January 2026 head-to-head test showed that leading tools each missed errors—CodeRabbit caught many issues yet overlooked some injected defects, while Augment caught all injection errors but had a poor UX (YouTube: @Samuel Gregory, 2026-01-08). AI works best as a first-pass filter that speeds up human reviewers, not as a replacement for them.

Which free option should I choose for a personal project, an open-source repo, or a team?

For a personal project, zzzcode.ai or a HeFu-backed CLI script is fastest. For an open-source repo, CodeRabbit's OSS free tier offers the most polished GitHub integration. For a team that needs data control, self-host PR-Agent (Apache 2.0 since April 2026) or build a custom reviewer on HeFu's API so you can switch between Claude Sonnet 5, GPT-5 Codex, or DeepSeek-V4-Pro as requirements change.

Is it safe to send proprietary code to a free AI review tool?

Not always. Free tools may use submitted code for model training or analytics, and third-party servers add exposure. For proprietary code, prefer self-hosted open-source review or a paid API with clear data-retention terms; HeFu's documentation details the API's request-handling model as of September 2026, and the official pricing page lists enterprise options.

How do I build a custom AI code review bot with HeFu?

Point your GitHub Action, GitLab CI job, or local script at HeFu's OpenAI-compatible endpoint https://api.hefu.hk/v1, select a model from the catalog as of September 2026—Claude Sonnet 5 for critique quality, DeepSeek-V4-Pro for cost efficiency—and post the model's output as inline PR comments. The integration steps match our Cline VS Code custom provider guide, and rates are available on the pricing page.

👉 免费注册 HeFu / Sign up free

AI Amazon Listing Generator: The Definitive Guide for 2026

mpoper — Sun, 20 Sep 2026 02:13:35 +0000

AI Amazon Listing Generator: The Definitive Guide for 2026

Key Takeaway: What Every Seller Needs to Know

AI-powered Amazon listing generators have moved from experimental to essential: as of Sep 2025 — per CNBC's Sep 17, 2025 report — Amazon's own tooling already helps 1.3 million third-party sellers generate roughly 70% of each listing's content, and AI-assisted workflows compress what once took hours into minutes. But no seller should publish unedited output, because hallucinations, trademark slips, and compliance errors still demand human review before anything goes live.

How AI Listing Generators Work: A Technical Overview

Most listing generators are built on large language models (LLMs) fine-tuned or prompt-engineered for e-commerce copy. Inputs typically include a keyword list, product features and specifications, brand tone, and sometimes an existing ASIN or product photo. Outputs follow Amazon's standard structure: a title within the 200-character maximum (Amazon style guide, as of 2025), five bullet points (up to 500 characters each in most categories), a product description, and backend search terms (up to 250 bytes in most categories).

Newer tools add multimodal generation: from a single product image, they claim to produce infographics, lifestyle shots, A+ content modules, and video scripts. One such vendor, Listing Optimization AI, reports (self-reported figures, as of Sep 2026) that it has served 1,000+ brands and 100+ agencies, generating 3 main-image options, 4–6 infographic layouts, 2 lifestyle scenes, 1 A+ content plan, and 1 video script from a single ASIN or photo.

The quality ceiling depends heavily on which model powers the tool. That is why API gateways are gaining traction among agencies: HeFu exposes a single endpoint at https://api.hefu.hk/v1 that routes requests across GPT-5.6, Claude Opus 5, DeepSeek V4, Kimi K3, and Gemini 3.6 (HeFu models catalog, as of Sep 2026), letting sellers swap creative, analytical, and budget-tier models without rewriting code. Model availability changes as vendors ship new versions — refer to the models catalog for the current list.

Top Benefits of Using an AI Amazon Listing Generator

Speed at massive scale. According to a CNBC report (Sep 17, 2025), Amazon's generative AI listing tool, adopted by 1.3 million third-party sellers, can generate about 70% of a product listing's content, compressing what once took hours into minutes.

Measurable conversion lift. Amazon's Ads Console AI Creative Studio produces ad creatives in 5–10 minutes (as of 2025; Amazon Ads Blog), and click-through rates are reported up to 40% higher than manual creatives (Xneeti, 2026 review). For sellers running sponsored products, this directly improves the economics of each listing.

Marketplace economics demand it. Third-party sellers contribute roughly 60% of Amazon's unit sales — more than half, per CNBC (Sep 17, 2025), and consistent with Amazon's own ~60% disclosure, as of 2024. With that much competition, the ability to produce localized, keyword-optimized listings at scale is no longer a nice-to-have.

Multilingual and multi-marketplace coverage. API-based generators can reformat content for Amazon.com, .co.uk, .de, and .jp in one pass, adjusting for local search behavior, character limits, and compliance phrasing (marketplace-specific limits are documented in each site's style guide; see Seller Central).

Critical Features to Look for in a Listing Generator

SEO keyword integration: genuine use of search-term harvesters and backend keywords — remember the 250-byte backend-field limit, per Amazon's style guide (as of 2025) — not just title stuffing.
Tone and brand-voice control: the ability to shift from "technical spec sheet" to "lifestyle storytelling."
Policy-compliance filters: automatic flagging of prohibited claims and restricted words.
Batch processing: generating dozens of listings in a single run for multi-SKU catalogs.
Marketplace variation support: character limits and taxonomies differ per region (e.g., the 200-character title maximum applies on Amazon.com and .co.uk, with localized variations elsewhere).
Multimodal output: decide whether you need images and A+ modules or text-only copy.
Model selection: per the HeFu models catalog, different models suit different stages — GPT-5.6 for punchy bullets, Claude Opus 5 for long-form A+ narrative, DeepSeek V4-Flash for high-volume drafts at minimal cost, and Gemini 3.6 Flash for grounding copy in image inputs. Model availability and naming change as vendors ship new versions; refer to the catalog for the current list.

Comparison of Leading AI Listing Generators (As of Sep 2026)

Tool	Output scope	Pricing (as of Sep 2026)	Amazon integration	Best fit
Amazon Seller AI tools (listing generator, Seller Assistant, AI Creative Studio)	copy + ad images	Free	Native (Bedrock / Ads Console)	Beginners needing a compliant baseline
CopyMonkey	text-only (title, bullets, description)	~$33–99/month (StoreClaw, 2026)	Manual copy-paste	Mid-tier sellers focused on copy speed
Keyword research suites (Helium 10-class)	keyword data + AI-assisted copy	~$40–230/month (StoreClaw, 2026)	Manual, semi-automated	Sellers who need keyword depth first
Ecomtent	agency-grade content + A+ modules	from ~$450/month (StoreClaw, 2026)	Manual / team workflow	Brands with larger content budgets
HeFu API gateway	copy, image understanding, A+ narrative, model routing	Usage-based / subscription — see official pricing page	Unified API for multi-platform pipelines	Developers and agencies serving many storefronts

Pricing and feature details above reflect vendor pages and third-party roundups at the time of writing; confirm current rates on each vendor's official pricing page before committing.

For a deeper side-by-side of these categories, see our 2026 AI Listing Generator Playbook and the free-tool guide that tests what actually works.

Potential Pitfalls and How to Avoid Them

Hallucinated product details. LLMs invent specifications when inputs are thin — weights, materials, dimensions appear confidently but falsely. Mitigation: always feed a structured spec sheet (e.g., CSV or JSON with required fields) and instruct the model to leave gaps rather than guess.

Trademark misuse. AI frequently generates "Apple-compatible" or "Brand X style" phrasing that violates Amazon's trademark and title policies. Amazon's title policy also restricts promotional phrases and special characters — review against the current style guide before publishing.

Unverifiable image text. Tools that render infographics can place numbers or claims on images that were never fact-checked. Seller-community reports across 2025–2026 cite this as one of the most common sources of listing suspensions — verify every on-image claim against the physical spec sheet.

Compliance overreach. Claims like "cures," "#1 rated," or FDA-adjacent statements require human legal judgment, not model confidence. Amazon's prohibited-claims and restricted-products policies apply equally to AI-generated copy (Seller Central).

Platform drift. Amazon updates its listing policies regularly; third-party SaaS tools lag. Always validate output against the current Amazon style guide before publishing.

Rule of thumb: treat AI output as a first draft. Amazon's own Seller Assistant can automate multi-step operational tasks, but final accountability stays with the seller (CNBC, Sep 17, 2025).

Best Practices for Combining AI with Human Optimization

Start with a curated keyword list — AI cannot invent demand where none exists. Pull from search-term harvesters and backend keyword reports first.
Request 2–3 tone variants from the model for each listing and choose deliberately.
Verify every factual claim against the physical product spec sheet — cross-check weights, materials, and dimensions field by field.
Use batch generation for variants such as size, pack, and color variations.
Run A/B tests between human-written and AI-assisted listings on low-traffic units; measure conversion lift before scaling.
Swap models per pipeline stage — an API gateway makes this trivial: one key, one base URL at https://api.hefu.hk/v1, and the freedom to route titles through GPT-5.6, descriptions through Claude Sonnet 5, and bulk drafts through DeepSeek V4-Flash depending on cost and quality targets (model names per the HeFu models catalog, as of Sep 2026).

Conclusion: Choosing the Right AI Amazon Listing Generator

The decision criteria as of Sep 2026 are: (1) output scope — text-only, images, or full A+; (2) monthly budget; (3) integration depth with Amazon; (4) accuracy and compliance controls; and (5) the ability to switch models as new versions ship. Re-verify any of these criteria against the cited official pages before committing, since feature sets and prices change quickly.

Amazon's free tools cover roughly 70% of listing content for basic sellers (CNBC, Sep 17, 2025), which is a genuine baseline. Paid SaaS and API tools earn their cost through keyword depth, multi-marketplace coverage, multimodal output, and model flexibility. For agencies and developers, the HeFu gateway offers access to GPT-5.6, Claude Opus 5, DeepSeek V4, and Kimi K3 through one API, with current rates on the official pricing page. Whatever path you choose, keep a human in the loop: the best 2026 workflows are human-directed, AI-drafted, and data-verified.

FAQ

Does Amazon's free AI listing tool make paid tools unnecessary?

Not entirely. Amazon's built-in generator, used by 1.3 million sellers as of Sep 2025 per CNBC, handles roughly 70% of listing content — excellent for fast baseline drafts. Paid tools and API gateways add keyword research depth, tone control, A+ content design, batch operations across multiple storefronts, and the ability to test different LLMs. If you sell on Amazon only and your margins are thin, free tools may suffice; if you sell across platforms or need differentiation, the incremental cost is usually justified.

Can AI generators output images, A+ modules, and video scripts that are safe to publish?

Some tools do produce image and video variants — Listing Optimization AI, for example, states (self-reported, as of Sep 2026) that it generates 3 main-image options, 4–6 infographics, 2 lifestyle scenes, 1 A+ content plan, and 1 video script from a single ASIN or photo. However, the numbers and claims rendered inside images must be verified manually; as of 2026, no tool guarantees pixel-level factual accuracy. Always cross-check on-screen text against the product spec sheet before publishing.

How much do AI Amazon listing generators really cost in 2026?

As of Sep 2026, the public range is wide: Amazon's official tools are free; keyword research suites run roughly $40–230/month; CopyMonkey runs about $33–99/month; agency-level content platforms like Ecomtent start around $450/month (StoreClaw, 2026). An alternative is usage-based API access through a gateway like HeFu, where you pay per request and can route bulk drafts to lower-cost models such as DeepSeek V4-Flash. Current rates are available on the official pricing page.

Is there a free trial?

Most SaaS tools offer one — CopyMonkey and similar platforms typically provide 7-day or limited-generation trials, and Amazon's AI features are permanently free inside Seller Central. HeFu offers usage-based access through its API, with setup guidance in the development docs; check the pricing page for current allowances and trial terms, since free-trial terms change frequently — confirm on the vendor's site before signing up.

Can AI listing generators integrate directly with Amazon Seller Central?

Amazon's own tools do, natively. Most third-party SaaS tools do not — they generate text that you copy into Seller Central manually. An API gateway like HeFu (https://api.hefu.hk/v1) integrates with your own systems rather than with Seller Central directly, which is actually an advantage if you manage multiple sales channels and want one content pipeline feeding all of them.

👉 免费注册 HeFu / Sign up free

HeFu vs OpenRouter: Which Is Better? A Comprehensive Comparison

mpoper — Fri, 18 Sep 2026 08:10:03 +0000

HeFu vs OpenRouter: Which Is Better? A Comprehensive Comparison

Executive Summary & Direct Verdict

As of September 2026, neither HeFu nor OpenRouter has published latency, availability, or end-to-end performance benchmarks that a third party can independently reproduce, so this comparison is bounded by each platform's official product documentation and official pages rather than by a shared test dataset. For developers in the Asia-Pacific region and other markets underserved by US AI providers whose primary goal is production deployment, HeFu's positioning is more direct: an OpenAI-compatible entry point, a single unified bill, and access to multiple model families through Hong Kong nodes, with the official model catalog at https://hefu.hk/models. If your top priority is model coverage breadth and free-trial exploration, OpenRouter's aggregated model directory is the richer entry point (https://openrouter.ai/models). The "5.5% credit surcharge" and "free models dropped from 20 to 14" figures from an earlier draft could not be confirmed in OpenRouter's official pricing or model documentation, so this article does not retain them as verified data; refer to the real-time status of the OpenRouter official documentation and model page for those details.

Product Overview

HeFu's official documentation describes the service as an API gateway that aggregates multiple model providers under one unified access endpoint, https://api.hefu.hk/v1 (https://hefu.hk/docs). The official model page lists a matrix covering OpenAI, Claude, DeepSeek, Kimi, Gemini, plus Chinese model families such as Qwen, GLM, Seed, Grok, and MiniMax; however, whether each model is callable, its version number, and its pricing method all adjust with upstream providers, and the final authority is https://hefu.hk/models and https://hefu.hk/pricing.

OpenRouter officially defines its service as a unified OpenAI-compatible API for accessing multiple model providers (https://openrouter.ai/docs). Its model page displays a large catalog and attaches :free labels to some models; those labels, rate limits, and availability are dynamically configured by upstream providers. OpenRouter does not publish "free model count" as a stable API or contractual commitment, so any fixed count only represents a snapshot at a given moment and should not be treated as a long-term guarantee.

Pricing and Plans

OpenRouter uses a credit wallet and pay-as-you-go billing; terms for credit purchases, platform fees, refunds, and minimum top-up amounts are documented at OpenRouter official documentation / Credits. The "5.5% platform fee" from the earlier draft cannot be traced back to those official pages, so this article does not list it as fact. Self-hosted gateways such as LiteLLM are MIT-licensed, and the official repository states support for 100+ mainstream models (GitHub: BerriAI/litellm) with no per-token intermediary markup; however, self-hosting means you bear server, key management, availability, and upgrade costs yourself.

HeFu publishes per-model official list prices (USD) on its public model page. As of September 2026, the authoritative references are the model page and the pricing page. HeFu's packaging logic is "one account, one bill," and its official pages do not display OpenRouter-style credit purchase surcharges.

Model Catalog and Availability

OpenRouter's catalog advantage is breadth, including many long-tail models and community-uploaded models; its real-time directory is at https://openrouter.ai/models. That breadth carries stability risk: whether a model is available, whether it is free, and whether it is rate-limited are all decided upstream, with OpenRouter acting as a forwarding layer. Teams depending on :free models should expect replacement or throttling at any time and should not treat any free model as a stable production dependency.

HeFu's catalog is at https://hefu.hk/models and is positioned as "curated" rather than "exhaustive." Models listed on the official page include the OpenAI GPT-5.6 series, Claude Opus/Sonnet, DeepSeek V4, Kimi K3, Gemini series, and Chinese model families such as Qwen, GLM, Seed, Grok, and MiniMax. This article does not promise that unlisted models are available; additions and removals are governed solely by the official model page. For users in regions with restricted direct access to US AI providers, HeFu's official page describes its node solution as Hong Kong node access, but as of September 2026 there is no public third-party latency test to corroborate that description.

API Compatibility and Developer Experience

Both platforms offer OpenAI-compatible APIs, so tools such as Cline, Open WebUI, and LangChain can connect simply by changing the base URL.

HeFu's base URL is https://api.hefu.hk/v1, with configuration instructions at https://hefu.hk/docs. OpenRouter's OpenAI-compatible integration guide is at https://openrouter.ai/docs. If you use VS Code with Cline, the Cline VS Code Custom OpenAI-Compatible Provider Setup guide walks through the complete flow from configuring the provider to sending a request.

The real difference is in the operational contract: OpenRouter requires familiarity with credits, free-model routing, and upstream failover behavior, while HeFu provides a smaller curated catalog and its documentation emphasizes "one key, one bill, every model known-available." For teams that only need frictionless access to models such as GPT-5.6 or Claude Sonnet 5, a curated gateway usually reaches the first successful request faster, but the experience should still be validated against official documentation and your own real workload.

Performance, Latency, and Uptime

Any third-party gateway adds one hop between the application and the model provider; as an aggregated routing gateway, OpenRouter's architecture inherently includes one intermediate forwarding step (OpenRouter official documentation). That extra hop means additional latency, an additional data retention point, and an additional compliance review point. As of September 2026, OpenRouter has not published an auditable historical availability SLA; its service status page is https://status.openrouter.ai, which is not equivalent to a contractual guarantee.

HeFu's official documentation describes its nodes as Hong Kong nodes, which are theoretically closer to Asia-Pacific developers than US West Coast gateways, but HeFu has not published an official latency SLA or a third-party audit report. "Low latency" should therefore be read as product positioning rather than verified data. Actual round-trip time depends on local networks, carrier routing, model provider location, and current load; test with real workloads in your target region before making production decisions.

On aggregated routing performance: OpenRouter's Fusion-style features call multiple models at once and have a judge model integrate the results, so the cost is the sum of multiple inference runs; specific effects and pricing are subject to OpenRouter official documentation. "Half-price flagship performance" should not be a selection criterion, because fan-out does not reduce computational consumption.

Feature Comparison Table

Dimension	HeFu (as of September 2026, per official pages)	OpenRouter (as of September 2026, per official pages)
Core positioning	Curated production gateway, Hong Kong node access	Large multi-model aggregation router
Model catalog	Curated: GPT-5.6, Claude Opus/Sonnet, DeepSeek V4, Kimi K3, Gemini, Qwen, GLM, MiniMax, etc., see model page	Large catalog covering long-tail and community-uploaded models, see model page
Free tier	No free tier; US sign-up bonus for new accounts; billing rules see pricing page	Some models carry `:free` labels; the count is dynamic and not committed by the official pages
Fee structure	Per-model official list prices published on the model page; no credit purchase surcharge	Credit wallet and pay-as-you-go billing; platform fees per official documentation
API compatibility	OpenAI-compatible, `https://api.hefu.hk/v1`	OpenAI-compatible
Data path	Application → HeFu (Hong Kong node) → upstream	Application → OpenRouter → upstream (one extra hop)
Data retention control	See official documentation	See OpenRouter official documentation and privacy policy; ZDR availability depends on upstream providers
Best for	Asia-Pacific developers, production stability, unified billing	Experimentation, model breadth, free-model exploration

Use Case Recommendations

Independent developers and small teams in APAC and emerging markets: If the features described in HeFu's official documentation are available, a single key can access models such as GPT-5.6, Claude Sonnet 5, and DeepSeek V4-Flash, eliminating the overhead of managing multiple bills and multiple provider accounts. Configuration steps are in the HeFu official documentation and the Cline VS Code configuration guide. The same unified entry point also works for code generation, e-commerce copywriting, and other scenarios, such as the workflow examples in the Helium 10 Alternative for Amazon Listing Generation guide.
Enterprises with compliance requirements: Every aggregation gateway adds nodes to the data path. OpenRouter's specific data processing terms are in the OpenRouter official documentation and its privacy policy; ZDR (zero data retention) mode is available only when the selected upstream provider supports it and must be confirmed per account. HeFu's compliance narrative is shorter—fewer routing hops, Hong Kong nodes, and a clear model catalog—but this article is not legal advice; enterprises must validate data retention and cross-border transfer requirements through their internal compliance processes.
Multi-model routing enthusiasts: OpenRouter's Fusion-style aggregation features are technically interesting, but their cost is the stacking of multiple model calls and is not necessarily lower than directly calling a single flagship model (OpenRouter official documentation). If you mainly need to mix GPT-5.6, Claude Fable 5, and DeepSeek R1, HeFu handles this with one key and no fan-out. If you truly need long-tail model coverage, OpenRouter's catalog breadth remains hard to replace; for changes in Chinese-model free tiers and alternatives, see the OpenRouter Alternatives for Chinese Models guide.

FAQ

Which platform is more affordable, HeFu or OpenRouter?

As of September 2026, OpenRouter's specific credit purchase platform fees are subject to the official documentation; the "5.5%" figure from the earlier draft was not confirmed by official sources, so this article does not repeat it. HeFu publishes per-model official list prices (USD) on its public model page; authoritative references are the model page and the pricing page. Self-hosted solutions such as LiteLLM have no intermediary markup, but you must account for server, operations, and availability costs. The cheapest platform depends on your monthly token volume, regional network conditions, model types, and engineering time costs, not on any single percentage.

Which platform offers better model variety?

OpenRouter is significantly broader in model coverage; the real-time catalog is at https://openrouter.ai/models. Its free model count is a dynamic status, and any fixed number may become outdated; the :free labels on the model page are authoritative. HeFu offers fewer curated models—GPT-5.6 series, Claude Opus/Sonnet, DeepSeek V4, Kimi K3, Gemini, Qwen, GLM, MiniMax, etc.—each subject to the official model page. If you value the number of models you can try, OpenRouter fits better; if you value the number of models you must evaluate before launch, HeFu saves more time.

Do HeFu and OpenRouter both support OpenAI-compatible APIs?

Yes. Both platforms publicly provide OpenAI-compatible interfaces. HeFu's base URL is https://api.hefu.hk/v1 (official documentation), and OpenRouter's integration method is in its official documentation. Tools such as Cline, Open WebUI, and LangChain usually require only replacing the base URL and API key; field-level differences should still be verified in a test environment.

Are my prompts stored or used for training on these platforms?

OpenRouter's storage, anonymous sampling, and zero data retention (ZDR) options are subject to its official documentation and privacy policy; whether ZDR is available also depends on upstream provider support. HeFu's data retention policy is documented at https://hefu.hk/docs. This article cannot replace enterprise privacy and compliance review; rely on formal written terms and data processing agreements.

Why did OpenRouter's free model list drop from 20 to 14, and what should developers use instead?

The earlier draft's "dropped from 20 to 14" and "Meta Llama and Qwen free tiers removed" claims could not be traced to a historical snapshot on openrouter.ai official pages, so this article does not treat them as verified facts. Free model additions and removals are typically decided by upstream providers, and OpenRouter does not commit to any free model being permanently available. Developers needing low-cost or free models should check the current :free labels on the OpenRouter model page, or consider unified gateways such as HeFu and self-hosted proxies like LiteLLM. For a deeper comparison, see the OpenRouter Alternatives for Chinese Models guide.

👉 免费注册 HeFu / Sign up free

Free AI Listing Generator for Amazon Sellers: What Actually Works in 2026

mpoper — Mon, 14 Sep 2026 20:10:02 +0000

Free AI listing generators are a practical starting point for Amazon sellers who need to draft product titles, bullet points, and descriptions quickly, but they are not a complete solution. As of September 2026, most "free" generators deliver only truncated previews or title drafts — recent comparison tests show truncated previews are the norm — and nearly every output must be manually fact-checked, keyword-tuned, and reformatted to match Amazon's style guidelines before publishing. Treat these tools as a first-draft engine, not a publishing pipeline.

What Is a Free AI Listing Generator for Amazon Sellers?

A free AI listing generator is a software tool that converts basic product inputs — a product name, a few keywords, or a product photo — into Amazon-ready copy such as titles, bullet points, and descriptions. Because the output is produced by large language models, the tool can reorganize your raw feature list into benefit-driven language that fits Amazon's listing format.

The category is broader than it looks. Some tools are standalone web apps; others are modules inside larger seller platforms. Critically, Amazon itself now offers an AI listing assistant inside Seller Central. As documented in the free AI listing generators guide at amzbase.com, that built-in tool accepts a few words, a product photo, or a URL, and generates an Amazon-style title plus attributes at no separate charge. It's the baseline every third-party "free" generator must be judged against (availability varies by marketplace; verify in your Seller Central account).

But "free" often means something different in practice. Recent comparison tests find that most free AI listing generators show only truncated previews, while the complete title, bullet points, and description remain locked behind a paywall. So the first question to ask isn't "is it free?" — it's "what, exactly, is free?"

Key Benefits of Using a Free AI Listing Generator

Even with those paywall issues, free generators deliver real value for sellers testing the waters or producing many listing variants.

Speed. A generator produces a listing draft in seconds, compared with roughly 30–60 minutes of manual writing per listing. Even a truncated preview serves as a useful outline.
Evaluation without commitment. You can judge output quality and workflow fit before paying for anything.
Broader keyword coverage. Many free generators suggest search terms, including long-tail phrases you may have overlooked.
Cheaper A/B testing. Because generation costs nothing, you can create multiple title and bullet variations and test which performs better. Our 2026 AI Listing Generator Playbook walks through this testing workflow step by step.

Limitations to Watch Out For

The weaknesses of free listing generators are well documented — and 2026 testing confirms they haven't gone away.

Incomplete output is the norm. In 2026 roundups of free AI tools — such as sellercards.com's nine-tool test — only a minority of free tools could generate a complete, submittable listing with title, five bullet points, and description; most stop at keyword suggestions or partial drafts.

Generic wording hurts conversion. Free models tend to lean on bland phrases such as "high-quality material" or "perfect for everyday use." Without specific, keyword-rich details, a listing will struggle to rank and convert.

Hallucinated details are a real risk. AI models can invent specifications, dimensions, or compatibility claims. Every fact needs to be verified against your actual product data, since inaccurate listings lead to negative reviews and refund disputes.

Amazon style compliance is not automatic. Amazon enforces strict rules on title length (tightened to 75 characters in many non-media categories in July 2026; check your category in Seller Central), bullet point limits, capitalization, and prohibited words. Generated copy may include wording like "best" or "cheap," which Amazon may suppress in search — so a compliance pass is non-negotiable before publishing. Check your category's current style guide in Seller Central for the authoritative limits as of 2026.

Comparison: Free AI Listing Generators vs. Paid Tools

Dimension	Free Third-Party Tools	Paid Tools	Amazon Seller Central AI
Output completeness	Truncated preview or title draft; only a minority of free tools deliver full listings	Full title + 5 bullets + description	Full Amazon-style title + attributes
Cost model	Free at sign-up; full output behind paywall	Paid subscription or per-use pricing	No separate charge for sellers
Keyword research depth	Basic suggestions at best	Deep keyword data, search volume, and trend history	Limited to the inputs you provide
Independence	Tied to a third-party platform; output may be watermarked	External, but you control your data	Native to Seller Central; no model choice

The 2026 free vs. paid analysis at reviewiq.listaikit.com comes to a blunt conclusion: don't pay for a listing generator. The reasoning is straightforward — Amazon's built-in AI assistant already covers the basics at no charge, and sellers who need more power are better served by investing in a controllable AI workflow or dedicated keyword research than by subscribing to a single-purpose generator.

That market shift is visible in the numbers. Helium 10 — a long-time favorite for Amazon sellers — keeps its AI listing feature in the spotlight, but even its most useful features require a paid plan for anything beyond minimal usage. Meanwhile, sellers are realizing that the real competitive advantage doesn't come from a magic listing generator; it comes from understanding your niche, having solid keyword data, and building a repeatable review process for AI output.

Practical Workflow: Making a Free Generator Work for You

If you're going to use a free generator, use it with a clear process:

Input rich product data. More than a product name — paste in every spec, dimension, material, and feature. The better your input, the less hallucination you'll see.
Generate multiple variants. Create 3–5 title/bullet sets. Free tools make this cheap.
Run a compliance pass. Strip out superlatives, banned words, and any claims you can't prove.
Fact-check every number. Compare output against your actual product datasheet.
Merge the best parts. Treat the generator as a collaborator, not an oracle — combine the strongest bullets from several drafts.

This workflow won't replace a skilled copywriter, but it will save you hours per listing while keeping quality acceptable.

The Bottom Line

Free AI listing generators are useful for kicking off your listing process, especially when combined with Amazon's own free AI assistant inside Seller Central. But "free" tools that hide their full output behind paywalls, coupled with the need for fact-checking and style compliance, mean they're not a shortcut to publishing. Use them to accelerate your first draft, then apply judgment, verification, and Amazon's style rules before you hit submit.

What tools have you tried? Have you found a free generator that actually gives you a complete listing? Share your experience in the comments — the Amazon seller community can always use more data points.

DEV Community: mpoper

How to Set Up Claude Code with a Third-Party API Endpoint

How to Set Up Claude Code with a Third-Party API Endpoint

Why Use a Third-Party API Endpoint for Claude Code

Prerequisites Before You Start

Choosing and Creating Your Hefu API Key

Configuration via Environment Variables

Verification: Testing the Third-Party Endpoint Connection

Troubleshooting Common Endpoint Setup Issues

Security and Best Practices for API Credentials

Comparison Table: Official Anthropic API vs. Hefu Third-Party Endpoint

FAQ

What is the exact API base URL I should use for Claude Code?

Do I need a different API key for the Hefu endpoint?

Can I switch back to the official Anthropic API later?

Why can't I point Claude Code directly at an OpenAI endpoint?

Where do I go if the endpoint works but responses are slow?

Cherry Studio OpenAI-Compatible Provider Configuration: A Step-by-Step Guide

Cherry Studio OpenAI-Compatible Provider Configuration: A Step-by-Step Guide

Why Configure an OpenAI-Compatible Provider in Cherry Studio?

Prerequisites: What You Need Before Starting

Obtaining Your HeFu API Key and Base URL

Adding a Custom OpenAI-Compatible Provider in Cherry Studio

Selecting Models from the Official Model Catalog

Testing and Verifying Your Configuration

Troubleshooting Common Configuration Issues

Best Practices for Security and Reliability

FAQ

Should the base URL be the root address or the full endpoint address?

After adding a custom provider, the model list is empty or reports "model not found". What should I do?

Can I use an Anthropic key in an OpenAI-compatible provider?

Which endpoint should I use: /v1/chat/completions or /v1/responses?

Is it safe to share my API key in team configuration files?

Claude API for Southeast Asia Developers: A Practical Guide (As of Sep 2026)

Claude API for Southeast Asia Developers: A Practical Guide (As of Sep 2026)

Core Conclusion

Why Southeast Asia Developers Are Adopting Claude API

Key Claude API Capabilities That Matter for SEA Teams

Infrastructure and Latency Reality for the SEA Region

Pricing and Currency Considerations for SEA Developers

Comparison: Official Claude API vs. HeFu Unified Gateway

Real-World Integration Patterns for SEA Use Cases

Getting Started with HeFu for Claude API Access

Common Pitfalls and Best Practices

FAQ

Can I use the Claude API directly in Vietnam, Indonesia, or Malaysia, and how do I pay in local currency?

What are the risks and cost differences of using OpenRouter or third-party relays instead of the official Claude API?

How can I confirm that the Claude API I purchased is the original official model and not a substituted version?

Do I need an Anthropic account or an official API key to use Claude API through HeFu?

ChatGPT and Claude API Without a US Card: A 2026 Guide

How to Access ChatGPT and Claude API Without a US Card (2026 Guide)

Core Conclusion: Bypass the US Card Barrier with HeFu's Global Gateway

The US Card Bottleneck: Why It Excludes Two-Thirds of the World

HeFu's Solution: Flexible Payments and Seamless Migration

Comparison: Direct API vs. HeFu Aggregated API

Getting Started: Sign-Up, Integration, and First API Call

Building Production-Ready Apps Using HeFu's Toolkit

FAQ

Can I pay for Anthropic's official Claude API without a US bank card?

What are the limits of card-free services like OpenRouter compared with official APIs?

Are the models on HeFu the same as the official versions?

Is there a free tier on HeFu?

Is it safe to use a third-party API gateway instead of a virtual card?

AI Office Tools That Work in Your Browser: A Practical Guide for 2026 Teams

AI Office Tools That Work in Your Browser: A Practical Guide for 2026 Teams

Why Browser-Based AI Office Tools Are Now the Default Choice

What to Look for in a Browser-Based AI Office Stack

Category Comparison: Word Processing, Spreadsheets, Slides, and Chat Assistants

Benchmark Snapshot: Task Completion Time With and Without AI

How an API-First Approach Powers Your In-Browser Office Workflows

Side-by-Side Model Selection for Office Tasks

Security and Privacy Considerations for Cloud Office Tools

Turning Office AI Into a Team-Wide Practice: Implementation Tips

Getting Started: Connecting Your Browser Tools to HeFu in Minutes

Pricing and Plans

Use Cases: Marketing, E-Commerce, HR, and Customer Support

Common Pitfalls and How to Avoid Them

FAQ

Do I still need separate OpenAI or Claude subscriptions if I use a browser's built-in AI assistant?

Can browser-based AI tools connect directly to sensitive data in Google Workspace or Microsoft 365?

Which endpoint should I use: `/v1/chat/completions` or `/v1/responses`?