DEV Community: TokenPAPA

China's Best AI Models, One API Key: DeepSeek, Qwen, MiniMax, Kimi & More

TokenPAPA — Tue, 11 Aug 2026 06:12:43 +0000

China's Best AI Models, One API Key

China's AI labs are building some of the world's most capable — and most cost-effective — models. DeepSeek. Qwen. MiniMax. Kimi. Each one leads in different ways: coding, bilingual understanding, long context, creative generation.

But for developers outside China, accessing them has traditionally been a maze: Chinese phone numbers, local payment methods, region restrictions, separate accounts for every provider.

TokenPAPA changes that. One API key gives you instant access to China's best AI models — plus GPT, Claude, Gemini and 30+ more — with no Chinese phone number required.

The One-Key Promise

Benefit	What It Means for You
One API Key	A single key for DeepSeek, Qwen, MiniMax, Kimi and 30+ models
No Chinese Phone Number	Sign up with email, Google, or GitHub — no SMS verification needed
OpenAI-Compatible	Works with the OpenAI SDK, and any OpenAI-compatible app or client
Global Low-Latency	Edge-optimized routing for developers worldwide
Pay-As-You-Go	No subscription, no commitment — pay only for what you use

Why China's AI Models Matter in 2026

Price-performance leadership — Chinese models like DeepSeek V4 have repeatedly pushed frontier pricing down by 90%+ compared to US counterparts.
Bilingual excellence — For Chinese-English applications, Chinese models are often the best choice.
Open-weight ecosystem — Many of the strongest open-weight models come from Chinese labs.
Specialized strengths — From coding agents to long-context reasoning, each lab has its own edge.

The catch used to be access. TokenPAPA removes the friction so you can actually use them.

What Developers No Longer Need

Before (Direct provider access)	With TokenPAPA
❌ Chinese phone number	✅ Email / Google / GitHub login
❌ Multiple accounts & keys	✅ One API key
❌ Region restrictions / VPN	✅ Global access
❌ Chinese payment methods	✅ Stripe, Waffo Pancake, cards
❌ Learning different API formats	✅ One OpenAI-compatible format

Get Started in 60 Seconds

Step 1 — Sign up at tokenpapa.ai with email, Google, or GitHub.

Step 2 — Create your API key in the console.

Step 3 — Call any model with the OpenAI SDK:

from openai import OpenAI

client = OpenAI(
    api_key="your-tokenpapa-key",
    base_url="https://tokenpapa.ai/v1"
)

# Same code, different models — switch with one line
for model in ["deepseek-v4-flash", "qwen3.8", "kimi-k3"]:
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Hello! Introduce yourself briefly."}]
    )
    print(f"{model}: {response.choices[0].message.content[:60]}...")

That's it. No Chinese phone number, no VPN, no separate accounts.

FAQ

Q: Do I need a Chinese phone number to use TokenPAPA?
A: No. TokenPAPA is built for global developers — sign up with email, Google, or GitHub and start calling Chinese AI models immediately.

Q: Is TokenPAPA compatible with the OpenAI SDK?
A: Yes. Set base_url to https://tokenpapa.ai/v1 and use your API key. Any OpenAI-compatible client or app works without modification.

Q: Which Chinese AI models can I access?
A: DeepSeek, Qwen, MiniMax, Kimi and more of China's leading models — plus GPT, Claude, Gemini and 30+ total, all through one key.

Start Today

Sign up at tokenpapa.ai — free credits on registration
Create your API key in the console
Call China's best AI models — one key, no phone number, pay-as-you-go

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/chinas-best-ai-models-one-api-key.

TokenPAPA Now Supports Google & GitHub One-Click Login (2026)

TokenPAPA — Mon, 10 Aug 2026 13:44:52 +0000

TokenPAPA Now Supports Google & GitHub One-Click Login

Logging into TokenPAPA just got a lot faster. The platform now supports Google and GitHub one-click login — no password, no email verification, no waiting.

Login Options Compared

Feature	Email + Password	Google One-Click	GitHub One-Click
Registration step	Required	Auto-created	Auto-created
Email verification	Required	Not needed	Not needed
Password to remember	Yes	No	No
Time to first login	~2-3 min	~10 seconds	~10 seconds
Security	Password	OAuth	OAuth

How to Log In with Google

Go to https://tokenpapa.ai/login
Click the Google icon at the bottom of the login form
Complete authorization on Google's page — you're logged in automatically

That's it. If it's your first time, a TokenPAPA account is created for you on the spot. No separate registration, no email code.

How to Log In with GitHub

Go to https://tokenpapa.ai/login
Click the GitHub icon at the bottom of the login form
Complete authorization on GitHub's page — you're logged in automatically

Same flow, same speed. First-time users get an account created automatically.

Why Developers Love One-Click Login

No password to manage — one less credential in your password manager
No email verification delay — start using the API immediately
Automatic account creation — skip the entire registration form
More secure — uses standard OAuth: TokenPAPA never sees or stores your Google/GitHub password
Perfect for CI/CD — GitHub login integrates naturally with developer workflows

Bind Google / GitHub to an Existing Account

Already have a TokenPAPA account? You can bind Google or GitHub to it:

Log in and go to Personal Settings
Find the Third-Party Account Binding section
Click Bind next to Google or GitHub
Complete authorization — your accounts are linked

After binding, you can use one-click login going forward while keeping all your existing tokens and balance.

FAQ

Q: Does logging in with Google or GitHub create a new account automatically?
A: Yes. Your first one-click login creates a TokenPAPA account automatically — no separate registration step.

Q: Can I bind Google or GitHub to an existing account?
A: Yes. Personal Settings → Third-Party Account Binding → Bind. All your tokens and balance stay intact.

Q: Is one-click login secure?
A: Yes. TokenPAPA uses standard OAuth — it never receives or stores your Google/GitHub password.

Get Started in Under a Minute

Go to https://tokenpapa.ai/login and click Google or GitHub
Your account is created automatically
Create an API key in the console
Start calling deepseek-v4-flash, gpt-5.6, claude-opus-4 and 30+ more models

from openai import OpenAI

client = OpenAI(
    api_key="your-tokenpapa-key",
    base_url="https://tokenpapa.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello from TokenPAPA!"}]
)
print(response.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/tokenpapa-google-github-login.

DeepSeek Price History 2024–2026: From Price Slasher to Price Hike — TokenPAPA Keeps Prices Stable

TokenPAPA — Sun, 09 Aug 2026 00:45:18 +0000

DeepSeek Price History 2024–2026: From Price Slasher to Price Hike

On August 6, 2026, DeepSeek dropped a surprise announcement: it plans to significantly raise overall prices for its API services.

For a company that spent two and a half years playing the "price slasher" — cutting prices more than ten times to undercut every competitor — this is a historic turning point.

Here is the complete price history, and why TokenPAPA keeps DeepSeek access stable for its users.

DeepSeek API Price Timeline (2024–2026)

Date	Event	Key Price Points (Input)
2024.04	DeepSeek-V2 API launch	Base pricing
2024.08	V2 price cut	¥0.1 / 1M tokens tier
2024.12	DeepSeek-V3 base pricing	¥0.5 / 1M input, ¥8 / 1M output
2025.02	Promo: V3 at 50% off, R1 at 25% off (off-peak hours)	¥0.25 / 1M input
2025.09 (early)	V3.1 partial price cut	¥0.5 / 1M input
2025.09 (late)	V3.2-Exp permanent ~80% cut	~¥0.1 / 1M input
2026.04.24	V4 series launch	—
2026.04.25	V4-Pro 25% promo	¥0.025 / 1M input
2026.04.26	Cache-hit input cut to 1/10 of launch price	—
2026.05	Off-peak 50% promo + peak-hour pricing (Beijing 14:00-18:00)	—
2026.06	V4 official pricing: V4-Pro ¥0.05/1M, V4-Flash ¥0.04/1M input	—
2026.08.01	V4-Flash public beta (OpenRouter data)	—
🔴 2026.08.06	Official announcement: significant overall price increase	—

The pattern is clear: from V2 (2024) to V4 Flash (2026), DeepSeek's strategy was aggressive discounts — often 50–90% off — to win market share. The August 2026 announcement marks the first major reversal: the "cheapest frontier model" era is ending.

Why Is DeepSeek Raising Prices?

Surging demand — V4-Flash became one of the most-called models globally within a week of launch; capacity is strained.
Compute costs — Training and inference at this scale (V4-Flash is a 284B-parameter model) is expensive; sustained below-cost pricing isn't viable forever.
Peak-hour strain — DeepSeek already experimented with peak-hour pricing; the hike formalizes load-based pricing.
Industry shift to "value pricing" — As Chinese AI media notes, the market is moving from pure price wars toward value-based pricing.

Experts note the timing is delicate: Meta's Muse Spark and GPT-5.6 Luna now offer competitive price-performance. DeepSeek's price hike tests whether its brand loyalty survives.

What This Means for Developers

Cost certainty is now a feature. With official DeepSeek prices going up, developers need a stable, predictable billing partner.
Model switching matters more than ever. When one provider's price changes, you want alternatives with zero migration cost.
Locking in current prices before the hike takes effect is the smart move.

✅ TokenPAPA Keeps Its Prices Stable

While DeepSeek raises official API prices, TokenPAPA maintains stable pricing and consistent service for DeepSeek models:

Same models, same quality — deepseek-v4-flash and deepseek-v4-pro remain available
Stable rates — TokenPAPA's pricing is set by the platform and remains unchanged in the short term (see our pricing page for current rates)
One key, 30+ models — if you ever want alternatives (Qwen3.8, Kimi K3, Mimo, GPT, Claude, Gemini), switch with a single line change
Recharge discounts — tiered top-up bonuses (up to 4% off) still apply

from openai import OpenAI

client = OpenAI(
    api_key="your-tokenpapa-key",
    base_url="https://tokenpapa.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",  # Stable pricing on TokenPAPA
    messages=[{"role": "user", "content": "Hello, is DeepSeek available here?"}]
)
print(response.choices[0].message.content)

FAQ

Q: When will DeepSeek's price increase take effect?

A: DeepSeek announced the plan on August 6, 2026 but hasn't published exact rates or a date. It advised users to plan usage ahead.

Q: Will my TokenPAPA costs go up?

A: Not in the short term. TokenPAPA keeps stable pricing for DeepSeek models. Check tokenpapa.ai/pricing for current rates.

Q: What alternatives do I have if I want to switch?

A: TokenPAPA gives you one key for 30+ models — Qwen3.8, Kimi K3, Mimo, GPT-5.6, Claude, Gemini, GLM and more. Switching is a one-line change.

Get Started

Sign up at tokenpapa.ai
Create your API key in the console
Call DeepSeek or any of 30+ models — stable pricing, stable service

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/deepseek-price-history-tokenpapa.

DeepSeek Is Raising API Prices — TokenPAPA Users Keep Their Discount (2026)

TokenPAPA — Fri, 07 Aug 2026 07:31:25 +0000

DeepSeek Is Raising API Prices — TokenPAPA Users Keep Their Discount

On August 6, 2026, DeepSeek announced it plans to significantly increase its API prices. The news hit Bloomberg, SCMP, The Next Web, and dozens of developer communities the same day — and it sent a familiar wave of anxiety through the developer world: is my LLM bill about to jump?

Here's the good news for TokenPAPA users: you're not affected in the short term. Your discounted DeepSeek access stays — same model, same API key, no migration required.

What DeepSeek Announced

Item	Detail
Announcement Date	August 6, 2026
What Was Said	API pricing will be raised "significantly"
Affected Services	DeepSeek API (V4 Flash / V4 Pro)
Exact New Prices	Not yet confirmed
Effective Date	Not yet announced
Official Channel	DeepSeek developer platform

DeepSeek didn't share exact numbers or a date yet, but the direction is clear: the era of ultra-low subsidized pricing is ending.

Why Is DeepSeek Raising Prices?

Surging demand — DeepSeek V4 Flash has become one of the most-used models worldwide, and its release-day (July 31) demand stretched capacity.
Rising compute costs — Running a high-traffic API at $0.14/1M input tokens is hard to sustain; industry watchers believe the cache-hit pricing in particular was subsidized to build adoption.
Margin pressure — With hardware and inference costs climbing, DeepSeek needs to move toward sustainable pricing.

The timing is notable: just weeks after its V4-Flash-0731 release and months after a 75% price cut on V4 Pro, the price signal has flipped.

What This Means for Developers

If you call DeepSeek directly, your unit costs may rise once the new pricing takes effect.
If you rely on DeepSeek for cost-sensitive workloads (batch processing, agent loops, content generation), the increase could add up quickly.
Budget planning becomes uncertain — which is exactly when a flexible, multi-model API gateway pays off.

TokenPAPA Users Keep Their Discount

For TokenPAPA users, the short-term picture is simple:

DeepSeek access on TokenPAPA continues at current discounted pricing. Same model names (deepseek-v4-flash, deepseek-v4-pro), same API key, same base URL — nothing changes for you.

✅ No migration needed
✅ No code changes
✅ Current discounted rates remain (see the TokenPAPA pricing / top-up pages for live rates)
✅ If DeepSeek's official price rises, TokenPAPA's aggregated access still gives you one flexible entry point

TokenPAPA works with multiple upstream channels, so your access to DeepSeek models is not tied to a single official price sheet.

Direct DeepSeek vs TokenPAPA: Why It Matters Now

	DeepSeek Official	TokenPAPA
DeepSeek V4 Flash / Pro	Yes	✅ Yes
Pricing	Rising (announced)	Current discounted rates
Model choice	DeepSeek only	30+ models (Qwen, Kimi, GPT, Claude, Gemini, Mimo…)
Switch models	N/A	One-line change
Single API key	—	✅ Yes
Overseas access	Regional restrictions	✅ No VPN needed

Even if DeepSeek's official price climbs, TokenPAPA gives you the flexibility to route around it — to Qwen3.8, Kimi K3, Mimo, or any of 30+ models — without touching your infrastructure.

Alternative Models to Consider (If Official Prices Keep Rising)

Model	Strength	Best For
Qwen3.8	Top-rated coding & general (Agentic Index #1)	Coding agents, general tasks
Kimi K3	2.8T open-weight flagship	Long-context, bilingual
Mimo	Extremely cheap, free TTS tier	Cost-sensitive batch work
GLM / MiniMax	Strong Chinese ecosystem	Multimodal, video

Switching on TokenPAPA is a one-line change:

from openai import OpenAI

client = OpenAI(
    api_key="your-tokenpapa-key",
    base_url="https://tokenpapa.ai/v1"
)

for model in ["deepseek-v4-flash", "qwen3.8-max", "kimi-k3"]:
    resp = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Hello!"}]
    )
    print(f"{model}: {resp.choices[0].message.content[:40]}...")

FAQ

Will the DeepSeek price increase affect my TokenPAPA account?

In the short term, no. TokenPAPA continues offering discounted DeepSeek access with the same model names and API key. Live rates are always shown on the TokenPAPA pricing and top-up pages.

Will TokenPAPA prices also rise?

TokenPAPA currently keeps its discounted DeepSeek pricing. If anything changes, updates are announced on the platform and blog — and with 30+ models on one key, you always have alternatives.

How do I lock in the current situation?

Create your API key at tokenpapa.ai and keep using deepseek-v4-flash / deepseek-v4-pro as usual. No migration, no code changes — just continue building.

Get Started

Sign up at tokenpapa.ai — free credits on registration
Get your API key from the console
Keep calling deepseek-v4-flash — still discounted, still one key, still 30+ models behind it

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Is DeepSeek still cost-effective through TokenPAPA?"}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/deepseek-price-increase-tokenpapa.

TokenPAPA Top-Up Bonus: Get Up to 4% Off on Every Recharge (2026)

TokenPAPA — Thu, 06 Aug 2026 02:40:39 +0000

TokenPAPA Top-Up Bonus: Get Up to 4% Off on Every Recharge

Recharging your TokenPAPA account just got cheaper. The higher the top-up amount, the bigger the discount — up to 4% off, applied instantly at checkout.

No codes, no steps, no waiting: the discount is automatic.

Recharge Discount Tiers

Top-Up Amount	Discount	You Pay
$50	1% off	$49.50
$100	2% off	$98.00
$200	3% off	$194.00
$500	4% off	$480.00

💡 How it works: the discount is a price reduction at checkout — you pay less, and your account receives the full top-up amount. For example, top up $50 and you only pay $49.50; your balance gets the full $50.

How to Top Up and Get the Discount

Log in to your account and open the top-up page: https://tokenpapa.ai/console/topup
Select an amount — $50, $100, $200, $500 (or a custom amount; discount tiers apply to the preset values)
Choose a payment channel:

Channel	WeChat Pay	Alipay	Apple Pay	Google Pay	Bank Card
Stripe	✅	✅	✅	—	✅
Waffo Pancake	✅	—	✅	✅	✅

Pay — the tiered discount is applied automatically before you confirm
Done — your balance updates instantly

Real Cost Examples

Here's exactly what you save at each tier:

Top-Up	Regular Price	Discount	You Pay	You Save
$50	$50.00	1%	$49.50	$0.50
$100	$100.00	2%	$98.00	$2.00
$200	$200.00	3%	$194.00	$6.00
$500	$500.00	4%	$480.00	$20.00

Tip: if you regularly spend $100+ on API calls, a single $500 top-up saves you $20 — and with DeepSeek V4 Flash priced from $0.14/1M tokens, that's thousands of extra requests.

Frequently Asked Questions

Do I need a code or coupon to get the discount?

No. The discount is applied automatically at checkout based on your top-up amount. Nothing to copy, nothing to enter.

Which payment methods qualify?

Both supported channels qualify — Stripe (WeChat Pay, Alipay, bank cards, Apple Pay) and Waffo Pancake (WeChat Pay, Apple Pay, Google Pay, bank cards).

When does my balance update?

Immediately after payment completes. You'll be redirected back to TokenPAPA and your balance is credited instantly.

Start Saving Today

Sign up at tokenpapa.ai — free credits on registration
Top up at https://tokenpapa.ai/console/topup
Get the discount automatically — and start calling 30+ models (DeepSeek, GPT, Claude, Gemini, Kimi, Qwen, Mimo) through one API

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello from TokenPAPA!"}]
)
print(resp.choices[0].message.content)

See also: TokenPAPA Payment Guide — Stripe & Waffo Pancake | Pricing

Originally published at https://doc.tokenpapa.ai/en/docs/blog/topup-recharge-bonus.

How to Top Up TokenPAPA: Stripe & Waffo Pancake Payment Guide (WeChat Pay, Alipay, Apple Pay, Google Pay, Cards)

TokenPAPA — Mon, 03 Aug 2026 03:08:37 +0000

How to Top Up TokenPAPA: Stripe & Waffo Pancake Payment Guide

Topping up your TokenPAPA account just got easier. TokenPAPA now supports two payment channels — Stripe and Waffo Pancake — covering WeChat Pay, Alipay, Apple Pay, Google Pay, and bank cards. Minimum top-up is only $10, and your balance is credited instantly after payment.

This guide covers every payment method, the step-by-step top-up process, and answers to common questions.

Payment Methods at a Glance

Payment Method	Stripe	Waffo Pancake
WeChat Pay	✅	✅
Alipay	✅	—
Bank Card	✅	✅
Apple Pay	✅	✅
Google Pay	—	✅
Minimum Top-Up	$10	$10
Balance Credit	Instant	Instant

Choose the channel that fits you:

Chinese users: WeChat Pay or Alipay through Stripe
Apple ecosystem: Apple Pay on either channel
Android / Google users: Google Pay through Waffo Pancake
Card holders: Any bank card on either channel

How to Top Up (Step by Step)

Log in to tokenpapa.ai and go to the Top Up page: https://tokenpapa.ai/console/topup
Enter an amount — select a preset amount or type a custom one (minimum $10)
Choose a payment channel — Stripe or Waffo Pancake
Pick your payment method — WeChat Pay, Alipay, bank card, Apple Pay, or Google Pay (depending on the channel)
Click "Top Up" — you'll be redirected to the payment platform
Complete payment — you'll be redirected back to TokenPAPA automatically
Done! — your balance updates instantly and you can start calling APIs right away

Which Channel Should I Use?

You want to pay with…	Best channel
WeChat Pay	Stripe or Waffo Pancake
Alipay	Stripe
Apple Pay	Stripe or Waffo Pancake
Google Pay	Waffo Pancake
Bank card	Stripe or Waffo Pancake

Both channels credit your balance instantly, so pick whichever payment method is most convenient for you.

Why Top Up on TokenPAPA?

One balance, 30+ models — your credits work across DeepSeek, GPT, Claude, Gemini, Kimi, Qwen, Mimo and more
No VPN / no Chinese phone required for overseas developers
Instant credit — no waiting, no approval
Low minimum — top up from just $10
Flexible payment — mobile wallets, cards, and bank payments all supported

Frequently Asked Questions

Can I pay with WeChat Pay?

Yes — WeChat Pay is supported through both Stripe and Waffo Pancake channels.

What is the minimum top-up?

The minimum top-up is $10 USD.

How long until my balance updates?

Instantly. After payment completes you're redirected back automatically and your balance is credited immediately.

Is there a fee for topping up?

Payment processing fees (if any) are shown on the payment page before you confirm. The amount you enter is the amount credited to your balance.

What if my payment fails?

Check that your card is enabled for international/online payments, or try the other payment channel (Stripe ↔ Waffo Pancake). If the problem persists, contact support@tokenpapa.ai or join our Telegram.

Getting Started

Sign up at tokenpapa.ai — free credits on registration
Top up at https://tokenpapa.ai/console/topup — from just $10, paid your way
Create an API key and start building with 30+ models

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/tokenpapa-payment-guide.

DeepSeek V4 Flash Official Release (0731): Agent Benchmarks Jump Past V4 Pro — Live on TokenPAPA

TokenPAPA — Sat, 01 Aug 2026 07:51:29 +0000

DeepSeek V4 Flash Official Release (0731): Agent Benchmarks Jump Past V4 Pro

On July 31, 2026, DeepSeek officially released DeepSeek-V4-Flash to public beta. The API calling convention is unchanged — set model to deepseek-v4-flash and you get the latest version.

The headline: agent capabilities are dramatically stronger, with benchmark scores that beat DeepSeek-V4-Pro-Preview across the board.

And the good news: TokenPAPA already supports the update. No code changes needed.

What's New in V4 Flash 0731

Aspect	Detail
Release	Official version, public beta
Model Name	`deepseek-v4-flash` (unchanged)
Architecture	Same structure/size as V4 Flash Preview
Change	Post-training refresh only
API	Chat Completions + native Responses API
Codex	Specifically adapted ✅

DeepSeek-V4-Flash-0731 keeps the same model structure and size as DeepSeek-V4-Flash-Preview — only the post-training was redone. The API interface was upgraded for V4 Flash only; V4 Pro API and APP/WEB models are unchanged, and the V4 Pro official release is coming soon.

Agent Benchmark Scores: Flash Beats Pro-Preview

The official release focuses on agentic coding and tool-use. Here are the published scores:

Benchmark	V4 Flash (0731)	vs V4 Pro Preview
Terminal Bench 2.1	82.7	Far ahead ✅
NL2Repo	54.2	Far ahead ✅
Cybergym	76.7	Far ahead ✅
DeepSWE	54.4	Far ahead ✅
Toolathlon (verified)	70.3	Far ahead ✅
Agent Last Exam	25.2	Far ahead ✅
Automation Bench (Public)	25.1	Far ahead ✅
DSBench-FullStack (internal)	68.7	Far ahead ✅
DSBench-Hard (internal)	59.6	Far ahead ✅

Note: For public Code Agent benchmarks, DeepSeek used the DeepSeek Harness minimal mode (upcoming release) with max settings, top_p=0.95, temperature=1.0. DSBench-FullStack is an internal full-stack dev test set; DSBench-Hard is an internal hard Coding Agent test set.

What this means: for agentic workloads — terminal automation, repo generation, cybersecurity tasks, full-stack development — the Flash tier now delivers flagship-class agent ability at Flash pricing.

What This Means for Developers

Cheapest agent model just got stronger — V4 Flash was already the budget workhorse ($0.14/1M input, $0.28/1M output, $0.0028/1M cache-hit input). Now its agent skills rival the Pro tier.
Responses API + Codex ready — native support means you can drop it into modern OpenAI tooling and Codex-style agent loops without translation layers.
No migration cost — same model name, same endpoint. Existing code keeps working.
Pro official version incoming — expect the V4 Pro refresh soon; Flash users get the upgrade today.

Try It on TokenPAPA Right Now

TokenPAPA already supports the updated deepseek-v4-flash — same API, same model name:

from openai import OpenAI

client = OpenAI(
    api_key="your-tokenpapa-key",
    base_url="https://tokenpapa.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",  # Latest official version
    messages=[{"role": "user", "content": "Write a Python script that scans a repo and summarizes TODO comments."}]
)
print(response.choices[0].message.content)

Using the native Responses API

response = client.responses.create(
    model="deepseek-v4-flash",
    input="List all open issues from this GitHub repo and suggest fixes.",
)
print(response.output_text)

Using it with Codex-style tool loops

# TokenPAPA is OpenAI-compatible, so Codex and similar agents work directly:
# 1. Set base_url to https://tokenpapa.ai/v1
# 2. Set model to deepseek-v4-flash
# 3. The agent handles function/tool calls natively

Why Access V4 Flash Through TokenPAPA?

One key, 30+ models — switch between DeepSeek, GPT, Claude, Gemini, Kimi, Qwen, Mimo with a single line change
No VPN / no Chinese phone required for overseas developers
OpenAI, Claude, and Gemini native formats all supported
Instant upgrade — the 0731 release is already live

Getting Started

Sign up at tokenpapa.ai — free credits on registration
Get your API key from the console
Call deepseek-v4-flash — you're on the latest official version today

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Explain your agent capabilities in one sentence."}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/deepseek-v4-flash-0731-release.

Kimi K3 API Guide: How to Access Moonshot's 2.8T Open-Weight Model (2026)

TokenPAPA — Thu, 30 Jul 2026 02:25:05 +0000

Kimi K3 API Guide: How to Access Moonshot's 2.8T Open-Weight Model

Kimi K3 is Moonshot AI's flagship 2.8-trillion-parameter model. This guide covers everything you need to integrate it through TokenPAPA's API.

Prerequisites

A TokenPAPA account
Your API key from the dashboard
OpenAI Python library (or any OpenAI-compatible SDK)

pip install openai

Basic Chat Completion

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

completion = client.chat.completions.create(
    model="kimi-k3",
    messages=[
        {"role": "system", "content": "You are a helpful AI assistant powered by Kimi K3."},
        {"role": "user", "content": "Explain the Mixture of Experts architecture in simple terms."}
    ],
    temperature=0.7,
    max_tokens=2048
)

print(completion.choices[0].message.content)

curl https://tokenpapa.ai/v1/chat/completions \
  -H "Authorization: Bearer *** \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "What makes Kimi K3 special?"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'


const client = new OpenAI({
  baseURL: 'https://tokenpapa.ai/v1',
  apiKey: 'your-tokenpapa-key',
});

const completion = await client.chat.completions.create({
  model: 'kimi-k3',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'What is Kimi K3?' },
  ],
});

console.log(completion.choices[0].message.content);

Streaming (Real-Time)

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

stream = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "Write a short poem about artificial intelligence."}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Multi-Turn Conversations

from openai import OpenAI

client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-tokenpapa-key")

messages = [
    {"role": "system", "content": "You are a knowledgeable coding assistant."},
    {"role": "user", "content": "Write a Python function to calculate fibonacci numbers."},
]

# First response
resp1 = client.chat.completions.create(model="kimi-k3", messages=messages)
answer = resp1.choices[0].message.content
print("Kimi K3:", answer[:100] + "...")

# Follow-up
messages.append({"role": "assistant", "content": answer})
messages.append({"role": "user", "content": "Now optimize it for performance using memoization."})

resp2 = client.chat.completions.create(model="kimi-k3", messages=messages)
print("Optimized:", resp2.choices[0].message.content[:100] + "...")

Long Document Analysis

Kimi K3 excels at long-context tasks. Here's how to analyze a large document:

# Load a long document
with open("research_paper.txt", "r") as f:
    document = f.read()

client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-tokenpapa-key")

response = client.chat.completions.create(
    model="kimi-k3",
    messages=[
        {"role": "system", "content": "Summarize the following research paper in 3 bullet points."},
        {"role": "user", "content": document}
    ],
    max_tokens=1024
)

print(response.choices[0].message.content)

Bilingual (Chinese-English) Mode

Kimi K3's strongest capability is seamless Chinese-English switching:

client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-tokenpapa-key")

response = client.chat.completions.create(
    model="kimi-k3",
    messages=[
        {"role": "user", "content": "Translate this to Chinese and explain: 'Attention is all you need' is a seminal paper in deep learning."}
    ]
)
print(response.choices[0].message.content)

Pricing

Channel	Price (Input/1M tokens)	Price (Output/1M tokens)
TokenPAPA	10% below official ✅	10% below official ✅
Moonshot AI (Official)	Higher	Higher

Kimi K3 via TokenPAPA costs 10% less than going direct to Moonshot AI. Plus, you get unified access to 30+ other models under one API key and one billing dashboard.

Error Handling

from openai import OpenAI, APIError, RateLimitError, APITimeoutError

client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-tokenpapa-key")

try:
    response = client.chat.completions.create(
        model="kimi-k3",
        messages=[{"role": "user", "content": "Hello!"}],
        timeout=30
    )
    print(response.choices[0].message.content)

except RateLimitError:
    print("Rate limited. Retrying with backoff...")
except APITimeoutError:
    print("Request timed out. The model may be under heavy load.")
except APIError as e:
    print(f"API error: {e.status_code} - {e.message}")

Model Switching Pattern

One of the biggest advantages of TokenPAPA is the ability to compare Kimi K3 with other flagship models without changing your code:

models = {
    "kimi-k3": "Moonshot flagship (2.8T, open-weight)",
    "gpt-5.5": "OpenAI flagship",
    "claude-opus-4": "Anthropic flagship",
    "deepseek-v4-pro": "DeepSeek flagship",
}

client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

for model_id, description in models.items():
    resp = client.chat.completions.create(
        model=model_id,
        messages=[{"role": "user", "content": "Solve: 25 * 47 + 13 * 29"}],
        max_tokens=256
    )
    print(f"\n{model_id} ({description}):")
    print(resp.choices[0].message.content)

Next Steps

Sign up at tokenpapa.ai — free account, $2 free credits
Try Kimi K3 — the 2.8T open-weight flagship at 10% below official pricing
Explore other models — switch between 30+ models from one API

Originally published at https://doc.tokenpapa.ai/en/docs/blog/kimi-k3-api-guide.

Kimi K3 Review: 2.8 Trillion Parameter Open-Weight Model — How It Compares to GPT-5.5 & Claude Opus 4

TokenPAPA — Thu, 30 Jul 2026 02:25:04 +0000

Kimi K3 Review: 2.8 Trillion Parameter Open-Weight Model

On July 16, 2026, Moonshot AI changed the LLM landscape. They released Kimi K3 — a 2.8-trillion-parameter Mixture-of-Experts model that is the world's first open-weight 3T-class model.

Eleven days later (July 27), they made good on their promise: the full weights were published on HuggingFace for anyone to download.

This review covers what Kimi K3 is, how it performs, how much it costs, and how you can access it through TokenPAPA.

What Makes Kimi K3 Special

Specification	Kimi K3
Parameters	2.8 trillion (MoE)
Architecture	Mixture of Experts
Release Date	July 16, 2026
Weights	Open (HuggingFace, July 27)
Context Window	128K native
OpenAI Compatible	Yes

Kimi K3 is Moonshot AI's leap from the mid-range to the flagship tier. Their previous model (Kimi K2) was a strong contender in the budget-to-mid-range segment, but K3 aims squarely at GPT-5.5, Claude Opus 4, and DeepSeek V4 Pro.

How Kimi K3 Compares to the Competition

Model	Parameters	Open Weight	Context	Price (Input/1M)
Kimi K3	2.8T MoE	✅ Yes	128K	Lowest
GPT-5.5	~2T (est.)	❌ No	2M	$15.00
Claude Opus 4	~1T (est.)	❌ No	200K	$15.00
DeepSeek V4 Pro	~1T (est.)	✅ Yes	128K	$0.28
Kimi K2.6	~100B (est.)	❌ No	128K	$0.50

Price Advantage on TokenPAPA

Kimi K3 on TokenPAPA is 10% cheaper than official Moonshot AI pricing. And since you access it through a unified API, you can switch between Kimi K3 and any other model — GPT, Claude, DeepSeek, Gemini, Mimo — with a single line change.

Benchmark Positioning

Based on independent community benchmarks, Kimi K3 positions itself as follows:

Benchmark	Kimi K3	GPT-5.5	Claude Opus 4	DeepSeek V4 Pro
MMLU	Top tier ✅	Top tier ✅	Top tier ✅	Top tier ✅
Reasoning	Strong	Excellent	Excellent	Strong
Coding	Strong	Excellent	Excellent	Strong
Long Context	Leading ✅	Good	Good	Good
Bilingual (ZH/EN)	Excellent ✅	Good	Moderate	Excellent ✅

Key takeaway: Kimi K3 is strongest on bilingual Chinese-English tasks and long-document understanding — areas where Moonshot AI has specialized since its founding. On general reasoning and coding, it competes with the top tier but may trail GPT-5.5 and Claude Opus 4 in specific benchmarks.

Why Open Weight Matters

Kimi K3 being open-weight is a game-changer for several reasons:

Self-hosting — Organizations with GPU clusters can run K3 locally for complete data privacy
Fine-tuning — Researchers can adapt the model weights for specialized domains
Transparency — The open-weight community can audit, test, and validate the model
No vendor lock-in — You're not tied to a single API provider

Note: At 2.8T parameters, self-hosting Kimi K3 requires serious infrastructure. For most developers, the TokenPAPA API route is the most practical option.

Quick Start: Access Kimi K3 via TokenPAPA

Since Kimi K3 is OpenAI-compatible, getting started is trivial:

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

response = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "Explain the significance of a 2.8 trillion parameter open-weight model."}]
)

print(response.choices[0].message.content)

Switching from Kimi K3 to Other Models

# Same code, different model name
models = ["kimi-k3", "gpt-5.5", "claude-opus-4", "deepseek-v4-pro"]

for model in models:
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Hello!"}]
    )
    print(f"{model}: {response.choices[0].message.content[:50]}...")

When to Use Kimi K3

Best For:

Bilingual applications (Chinese + English)
Long-document analysis (contracts, research papers, legal docs)
Cost-conscious flagship use — flagship performance at a discount
Open-weight enthusiasts who want API access to complement self-hosted experiments

Consider Alternatives For:

Single-language English tasks where GPT-5.5 may have an edge
Complex multi-step coding where Claude Opus 4 excels
Ultra-long context (1M+ tokens) where Gemini 3 leads
Budget batch processing where DeepSeek V4 Flash ($0.14/M) is far cheaper

Getting Started

Sign up at tokenpapa.ai — $2 free credits, no Chinese phone needed
Get your API key from the dashboard
Start using Kimi K3 — pay 10% less than official pricing

from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

# Test Kimi K3
resp = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "What makes you different from GPT-5.5?"}]
)
print(resp.choices[0].message.content)

Originally published at https://doc.tokenpapa.ai/en/docs/blog/kimi-k3-review.

Free TTS API 2026: Xiaomi Mimo Text-to-Speech, Voice Clone & Voice Design (Completely Free)

TokenPAPA — Wed, 29 Jul 2026 02:30:39 +0000

Free TTS API 2026: Xiaomi Mimo Text-to-Speech, Voice Clone & Voice Design

Good news for voice AI developers: Xiaomi's Mimo TTS models are now available on TokenPAPA — and they're completely free to use.

No token charges. No usage limits. No hidden fees. Just three powerful voice AI models at zero cost.

What's Available

Model	Purpose	Price
mimo-v2.5-tts	Standard text-to-speech	Free
mimo-v2.5-tts-voiceclone	Clone any voice from audio samples	Free
mimo-v2.5-tts-voicedesign	Design custom synthetic voices	Free

Model Breakdown

1. mimo-v2.5-tts — Standard Text-to-Speech

Convert written text into natural-sounding speech. Supports multiple voices, adjustable speed, and various output formats.

Use cases:

Voice assistants and chatbots
Audiobook generation
Accessibility tools
Content creation (video narration, podcasts)
Language learning apps

2. mimo-v2.5-tts-voiceclone — Voice Cloning

Upload a short audio sample (a few seconds of someone speaking), and the model generates speech in that exact voice. This is the only free voice cloning API we know of in 2026.

Use cases:

Personalized voice assistants
Dubbing and localization
Preserving voices for accessibility
Character voices for games

3. mimo-v2.5-tts-voicedesign — Custom Voice Design

Create completely synthetic voices by describing the characteristics you want — gender, age, accent, tone, and more. No audio sample needed.

Use cases:

Brand voice design
Synthetic narrators
Custom voice actors for media
Prototyping voice interfaces

Quick Start: Call Mimo TTS in 30 Seconds

Since Mimo TTS models are OpenAI-compatible, you can use any OpenAI SDK. Just change the base_url and model name.

Python

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Generate speech
response = client.audio.speech.create(
    model="mimo-v2.5-tts",
    voice="alloy",
    input="Hello! This speech was generated by Xiaomi's Mimo TTS model, completely for free.",
)

# Save to file
response.stream_to_file("output.mp3")

cURL

# Download speech as MP3
curl https://tokenpapa.ai/v1/audio/speech \
  -H "Authorization: Bearer *** \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mimo-v2.5-tts",
    "input": "This is free text to speech from Xiaomi Mimo.",
    "voice": "alloy",
    "response_format": "mp3",
    "speed": 1.0
  }' \
  --output speech.mp3

JavaScript


const client = new OpenAI({
  baseURL: 'https://tokenpapa.ai/v1',
  apiKey: 'your-tokenpapa-key',
});

const response = await client.audio.speech.create({
  model: 'mimo-v2.5-tts',
  voice: 'alloy',
  input: 'Free text to speech from Xiaomi Mimo on TokenPAPA.',
});

const buffer = Buffer.from(await response.arrayBuffer());
writeFileSync('speech.mp3', buffer);

Comparing Mimo TTS with Other Providers

Feature	Mimo TTS (Free)	OpenAI TTS	Google TTS	ElevenLabs
Price	$0	$0.015/min	$0.000004/char	$5/month+
Voice Clone	Yes (free)	No	No	Yes ($11/mo)
Voice Design	Yes (free)	No	No	No
OpenAI Compatible	Yes	Yes	No	No
Chinese Phone Needed	No	No	No	No
Multiple Languages	Yes	Yes	Yes	Yes

Bottom line: Mimo TTS on TokenPAPA is the only provider offering free voice cloning and voice design in 2026.

Sign Up and Start Speaking

Getting started takes less than a minute:

Sign up at tokenpapa.ai — no Chinese phone required
Get $2 free credits on signup (for non-TTS models)
Use Mimo TTS models at zero cost — they don't consume your credits

# Verify it works
from openai import OpenAI
client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

# Quick test — should respond in seconds
response = client.audio.speech.create(
    model="mimo-v2.5-tts",
    voice="alloy",
    input="Mimo TTS is completely free on TokenPAPA!",
)
response.stream_to_file("test.mp3")
print("✅ Speech generated! Check test.mp3")

All three Mimo TTS models are available at no cost on TokenPAPA as of July 28, 2026. Pricing may change in the future. Standard signup credits apply to non-TTS models only.

Originally published at https://doc.tokenpapa.ai/en/docs/blog/free-tts-api-mimo-xiaomi.

Mimo TTS API Guide: How to Use Xiaomi Text-to-Speech, Voice Clone & Voice Design (2026)

TokenPAPA — Wed, 29 Jul 2026 02:24:12 +0000

Mimo TTS API Guide: How to Use Xiaomi Text-to-Speech, Voice Clone & Voice Design

This guide covers everything you need to integrate Xiaomi's Mimo TTS models into your application. All three models are completely free on TokenPAPA.

Prerequisites

A TokenPAPA account (sign up free)
Your API key from the dashboard
Python 3.8+ with the OpenAI library

pip install openai

1. Basic Text-to-Speech (mimo-v2.5-tts)

The standard TTS model converts text to natural speech with multiple voice options.

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Basic speech generation
response = client.audio.speech.create(
    model="mimo-v2.5-tts",
    voice="alloy",
    input="Welcome to TokenPAPA! Xiaomi Mimo TTS is fast and completely free.",
)

# Save as MP3
response.stream_to_file("welcome.mp3")
print("✅ Speech saved to welcome.mp3")

curl https://tokenpapa.ai/v1/audio/speech \
  -H "Authorization: Bearer *** \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mimo-v2.5-tts",
    "input": "Xiaomi Mimo TTS is completely free on TokenPAPA.",
    "voice": "alloy",
    "response_format": "mp3",
    "speed": 1.0
  }' \
  --output speech.mp3

Available Voice Options

Voice	Description
`alloy`	Balanced, neutral voice
`echo`	Deeper, resonant tone
`fable`	Soft, storytelling style
`onyx`	Deep, authoritative voice
`nova`	Warm, friendly female voice
`shimmer`	Clear, bright voice

Adjusting Speed and Format

response = client.audio.speech.create(
    model="mimo-v2.5-tts",
    voice="nova",
    input="This is a slower, clearer narration example.",
    speed=0.8,                 # Speed: 0.25 to 4.0
    response_format="wav",     # mp3, wav, flac, opus
)

2. Voice Cloning (mimo-v2.5-tts-voiceclone)

Clone any voice from an audio sample. The model learns the unique characteristics of a speaker's voice and can generate new speech that sounds like them.

How It Works

Prepare your audio sample — a clean recording of 10–30 seconds of speech
Send it to the voice clone model with the text you want spoken
Receive the cloned voice output

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Read the reference audio file
with open("reference_speech.mp3", "rb") as f:
    audio_bytes = f.read()

audio_base64 = base64.b64encode(audio_bytes).decode("utf-8")

# Generate speech in the cloned voice
response = client.audio.speech.create(
    model="mimo-v2.5-tts-voiceclone",
    voice="alloy",  # Not used by clone model
    input="This speech is in the cloned voice! Listen to how natural it sounds.",
    extra_body={
        "reference_audio": audio_base64,
    }
)

response.stream_to_file("cloned_output.mp3")

Tips for best voice clone quality:

Use a quiet recording environment (no background noise)
Keep samples between 10–30 seconds
Use a consistent speaking pace
Avoid multiple speakers in one sample
Higher quality input = better clone output

3. Voice Design (mimo-v2.5-tts-voicedesign)

Create entirely synthetic voices by describing the characteristics you want. No audio sample needed.

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Design a custom voice by describing its characteristics
response = client.audio.speech.create(
    model="mimo-v2.5-tts-voicedesign",
    voice="alloy",
    input="Hello! I am a custom-designed voice created by Xiaomi Mimo.",
    extra_body={
        "voice_description": "A warm, friendly middle-aged male voice with a slight British accent. Calm and professional tone, suitable for corporate narration."
    }
)

response.stream_to_file("designed_voice.mp3")

Voice Design Parameters You Can Specify

Parameter	Examples
Gender	male, female, neutral
Age	young, middle-aged, elderly
Accent	British, American, neutral, Chinese
Tone	warm, professional, cheerful, serious, soothing
Style	conversational, authoritative, storytelling, instructional
Pitch	low, medium, high
Speed	slow, normal, fast

4. Streaming Audio (Real-Time)

All three Mimo TTS models support real-time audio streaming. This is useful for voice assistants, real-time translation, and live narration.

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Stream audio in real-time
with client.audio.speech.with_streaming_response.create(
    model="mimo-v2.5-tts",
    voice="alloy",
    input="This is streaming audio from Xiaomi Mimo TTS. It plays in real time.",
) as response:
    with open("streamed_speech.mp3", "wb") as f:
        for chunk in response.iter_bytes():
            f.write(chunk)

print("✅ Streaming complete")

5. Error Handling

from openai import OpenAI, APIError

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

try:
    response = client.audio.speech.create(
        model="mimo-v2.5-tts",
        voice="alloy",
        input="Hello, world!",
    )
    response.stream_to_file("output.mp3")

except APIError as e:
    print(f"API Error: {e.status_code} - {e.message}")
except Exception as e:
    print(f"Error: {e}")

Quick Reference

Model	Endpoint	Purpose	Cost
`mimo-v2.5-tts`	`/v1/audio/speech`	Standard TTS	Free
`mimo-v2.5-tts-voiceclone`	`/v1/audio/speech`	Voice cloning	Free
`mimo-v2.5-tts-voicedesign`	`/v1/audio/speech`	Voice design	Free

All models support: mp3, wav, flac, opus output formats.
Streaming support: Yes (SSE-based).

Next Steps

Sign up for TokenPAPA — free account, no Chinese phone needed
Get your API key from the dashboard
Try the code examples above — they cost nothing

Need help? The TokenPAPA API documentation covers every endpoint in detail.

Originally published at https://doc.tokenpapa.ai/en/docs/blog/mimo-tts-api-guide.

OpenAI-Compatibility Explained: How One API Connects to 30+ LLMs (DeepSeek, GPT, Claude, Gemini & More)

TokenPAPA — Tue, 28 Jul 2026 04:32:49 +0000

OpenAI-Compatibility Explained: How One API Connects to 30+ LLMs

If you've built anything with LLMs in 2026, you've used the OpenAI API format. It's become the de facto standard — /v1/chat/completions, messages array, model string, role/content pairs.

But here's the thing: that format isn't exclusive to OpenAI anymore.

DeepSeek, Claude, Gemini, Mimo, Qwen, GLM, Kimi, and dozens more providers now offer OpenAI-compatible APIs. This means you can access any of them using the same code, the same SDK, and the same integration pattern.

This guide explains how OpenAI-compatibility works, why it matters, and how you can use TokenPAPA to switch between 30+ models with a single line change.

What "OpenAI-Compatible" Actually Means

An API is "OpenAI-compatible" when it uses the same:

Endpoint: /v1/chat/completions
Request body: { model, messages, temperature, max_tokens, stream }
Response format: { id, object, choices: [{ message: { role, content } }], usage }
Authentication: Authorization: Bearer <key>
Streaming: SSE-based text/event-stream with data: {...} deltas

Here's what it looks like in practice:

# This works identically with ANY OpenAI-compatible provider

response = requests.post(
    "https://api.openai.com/v1/chat/completions",  # <-- Change this
    headers={
        "Authorization": "Bearer <key>",  # <-- Change this
        "Content-Type": "application/json"
    },
    json={
        "model": "gpt-4o",  # <-- Change this
        "messages": [{"role": "user", "content": "Hello!"}],
        "temperature": 0.7
    }
)

Replace the base URL, API key, and model name — and you're talking to a completely different provider.

The Multi-Provider Problem

Without a unified API, connecting to multiple LLMs looks like this:

┌─────────────────────────────────────────────────┐
│                   Your Application               │
├─────────┬─────────┬──────────┬────────┬─────────┤
│ OpenAI  │ DeepSeek│ Anthropic│ Google │ Xiaomi  │
│ SDK     │ SDK     │ SDK      │ SDK    │ SDK     │
├─────────┼─────────┼──────────┼────────┼─────────┤
│ openai  │ deepseek│ anthropic│ google │ xiaomi  │
│ .com    │ .com    │ .com     │ .com   │ .com    │
└─────────┴─────────┴──────────┴────────┴─────────┘

Five different SDKs. Five API keys. Five billing dashboards. Five authentication patterns. Five sets of rate limits.

Now imagine this:

┌─────────────────────────────────────────────────┐
│                   Your Application               │
├─────────────────────────────────────────────────┤
│                 OpenAI SDK                       │
├─────────────────────────────────────────────────┤
│               TokenPAPA (one URL, one key)       │
├─────────┬─────────┬──────────┬────────┬─────────┤
│ OpenAI  │ DeepSeek│ Anthropic│ Google │ Xiaomi  │
│         │         │          │        │         │
└─────────┴─────────┴──────────┴────────┴─────────┘

One SDK. One API key. One billing dashboard. Your code never changes.

Code Examples: The Power of One API

Python: Switching Between Models

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

completion = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Write a Python function to sort a list"}],
    temperature=0.7
)
print(completion.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Only the model name changes!
completion = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Write a Python function to sort a list"}],
    temperature=0.7
)
print(completion.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Same code, different model
completion = client.chat.completions.create(
    model="gemini-3.5-flash",
    messages=[{"role": "user", "content": "Write a Python function to sort a list"}],
    temperature=0.7
)
print(completion.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"
)

# Same code, different model
completion = client.chat.completions.create(
    model="mimo-v2.5-pro",
    messages=[{"role": "user", "content": "Write a Python function to sort a list"}],
    temperature=0.7
)
print(completion.choices[0].message.content)

JavaScript / Node.js


const client = new OpenAI({
  baseURL: 'https://tokenpapa.ai/v1',
  apiKey: 'your-tokenpapa-key',
});

// DeepSeek
const response = await client.chat.completions.create({
  model: 'deepseek-v4-flash',
  messages: [{ role: 'user', content: 'Translate this to French' }],
});

// Or switch to Claude — same code, change model name only
const response2 = await client.chat.completions.create({
  model: 'claude-sonnet-4-6',
  messages: [{ role: 'user', content: 'Translate this to French' }],
});

cURL (for quick testing)

# DeepSeek
curl https://tokenpapa.ai/v1/chat/completions \
  -H "Authorization: Bearer your-key" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-v4-flash","messages":[{"role":"user","content":"Hello"}],"temperature":0.7}'

# Claude
curl https://tokenpapa.ai/v1/chat/completions \
  -H "Authorization: Bearer your-key" \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-sonnet-4-6","messages":[{"role":"user","content":"Hello"}],"stream":true}'

# Gemini
curl https://tokenpapa.ai/v1/chat/completions \
  -H "Authorization: Bearer your-key" \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-3.5-flash","messages":[{"role":"user","content":"Hello"}],"temperature":0.7}'

Advanced Patterns with a Unified API

1. Cost-Optimized Routing

Use cheap models for simple tasks, expensive models for complex ones:

def get_completion(task_complexity, user_message):
    model = "deepseek-v4-flash" if task_complexity == "simple" else "claude-sonnet-4-6"

    client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")
    response = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": user_message}]
    )
    return response.choices[0].message.content

# Simple greeting → $0.00003
print(get_completion("simple", "Hi!"))

# Complex analysis → $0.015
print(get_completion("complex", "Analyze this financial report..."))

2. Fallback Chains

If one provider is down, try another automatically:

def robust_completion(messages):
    models = [
        "deepseek-v4-flash",    # Try DeepSeek first (cheapest)
        "gpt-5.4-mini",         # Fallback to GPT
        "claude-sonnet-4-6",    # Last resort
    ]

    client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

    for model in models:
        try:
            response = client.chat.completions.create(
                model=model,
                messages=messages,
                timeout=30
            )
            return response.choices[0].message.content
        except Exception:
            continue

    raise Exception("All providers failed")

3. A/B Testing Models

Test different models on the same input to compare quality:

def compare_models(prompt, models):
    client = OpenAI(base_url="https://tokenpapa.ai/v1", api_key="your-key")

    results = {}
    for model in models:
        response = client.chat.completions.create(
            model=model,
            messages=[{"role": "user", "content": prompt}]
        )
        results[model] = {
            "content": response.choices[0].message.content,
            "tokens": response.usage.total_tokens,
            "cost": calculate_cost(model, response.usage)
        }
    return results

Which Models Are Available?

TokenPAPA's unified API supports 30+ models across these providers:

Provider	Models	Price Range (Input)
DeepSeek	V4 Flash, V4 Pro	$0.14 – $0.28
Mimo (Xiaomi)	V2.5, V2.5 Pro	$0.08 – $0.12
OpenAI	GPT-5.5, GPT-5.4, GPT-5.4 Mini	$0.15 – $15
Anthropic	Claude Opus 4, Sonnet 4	$3 – $15
Google	Gemini 3.1 Pro, 3.5 Flash, 3 Flash	$0.25 – $10
Alibaba (Qwen)	Qwen 3.5 Flash, 3.5 Plus	$0.20 – $0.40
Zhipu AI (GLM)	GLM-5, 5.1, 5.2	$0.30 – $0.50
Moonshot (Kimi)	Kimi K2.6	$0.50
MiniMax	M2.5, M2.7, M3	$0.60 – $0.80
Tencent	Hunyuan HY3 Preview	$1.00

Why OpenAI-Compatibility Won

You might wonder: why did OpenAI's format become the standard instead of Anthropic's or Google's?

Three reasons:

First mover advantage — OpenAI launched the chat completions API first and captured developer mindshare
Simplicity — The /v1/chat/completions format with messages array is clean and intuitive
SDK ecosystem — The OpenAI Python and Node.js SDKs became the de facto tools for LLM integration

By adopting OpenAI-compatibility, every other provider — from DeepSeek to Google to Xiaomi — made it trivially easy for developers to try their models. No new SDK to learn. No migration project. Just a URL change.

Getting Started with TokenPAPA

Step 1: Sign up at tokenpapa.ai — no Chinese phone required, international developers welcome.

Step 2: Get your API key from the dashboard. You'll receive $2 in free credits to start.

Step 3: Install any OpenAI-compatible SDK and point it to TokenPAPA:

pip install openai

from openai import OpenAI

client = OpenAI(
    base_url="https://tokenpapa.ai/v1",
    api_key="your-tokenpapa-key"  # Replace with your key
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",  # Or any model you want to try
    messages=[{"role": "user", "content": "Hello, world!"}]
)

print(response.choices[0].message.content)

That's it. You're now connected to 30+ LLMs through one API.

Summary

Capability	Without TokenPAPA	With TokenPAPA
SDKs to install	5+ (one per provider)	1 (OpenAI SDK)
API keys to manage	5+	1
Billing dashboards	5+	1
Model switching	Rewrite code	Change 1 parameter
Fallback handling	Custom infrastructure	Built-in
New model adoption	New integration	Just the model name

One API. One key. Thirty models. Zero friction.

Originally published at https://doc.tokenpapa.ai/en/docs/blog/openai-compatibility-guide.