If you already use terminal coding agents but do not want a separate subscription for every model family, this setup is for you. AceDataCloud Coding Plan is a 30-day, Credit-metered API package, not an official Claude Code or Codex membership. The current public catalog starts with Coding Plus at 500 Credits during the promotion (400 base + 100 bonus), with a ¥99 CNY display anchor and a public USD price of $14.645677. The bonus is listed through November 30, 2026 (UTC+8).
The useful architectural choice is not “Which AI brand should run everything?” It is: Which protocol does each client speak, and which model should own each task? Coding Plan currently associates Claude Messages, OpenAI Responses, and OpenAI-compatible Chat Completions with one Coding Application, covering model families including Claude, GPT/Codex, GLM, Kimi, and DeepSeek. Exact model IDs and client compatibility remain dynamic.
Start with the protocol, not the model logo
A coding client and a model are separate decisions. The client controls the interaction loop, tool calls, file edits, and approvals. The API protocol controls how that client communicates with the model.
Use this routing rule:
| Client or integration need | Preferred protocol | Why |
|---|---|---|
| Claude Code and Anthropic-native integrations | Claude Messages | Preserves the request shape expected by Anthropic-style clients |
| Codex and response-oriented agents | OpenAI Responses | Matches newer response and agent workflows |
| OpenCode, Cursor, or a custom SDK that accepts an OpenAI-compatible provider | Chat Completions | Broad compatibility and simple integration |
Do not assume every client can use every model merely because the plan includes several model families. A valid combination requires three matches: the client must support the protocol, the Coding credential must include the API scope, and the selected model ID must be available for that protocol.
Minimum configuration and credential boundary
Create or select a Coding Application from the Coding Plan page and use its token. Keep that token in an environment variable rather than committing it to a repository:
export ACE_CODING_TOKEN="YOUR_CODING_APPLICATION_TOKEN"
First, inspect the live model directory:
curl https://api.acedata.cloud/v1/models \
-H "Authorization: Bearer $ACE_CODING_TOKEN"
The id value of each returned item is the string to pass as model. However, /v1/models is a global directory; its output is not automatically trimmed to your Coding credential. Cross-check an ID against your credential scope, chosen protocol, and client before adopting it.
For an OpenAI-compatible client, the smallest useful configuration is conceptually:
Base URL: https://api.acedata.cloud
API key: $ACE_CODING_TOKEN
Model: <an exact ID returned by /v1/models>
Protocol: OpenAI-compatible Chat Completions
For Claude Code, choose the documented Claude Messages integration instead of forcing an OpenAI-compatible route. For Codex, follow the Responses-oriented configuration. The Coding Plan integration center links the current instructions for Claude Code, Codex, Kimi Code, OpenClaw, OpenCode, Cursor, Cline, Aider, and other supported clients.
Split work by task rather than loyalty
A multi-model budget becomes useful when routing is explicit. A practical starting policy is:
- Repository planning and difficult refactors: assign a strong reasoning model and give it the relevant architecture files.
- Routine implementation and test generation: use a lower-cost model that follows instructions reliably.
- Second-pass review: switch model families so the reviewer is less likely to repeat the implementer's assumptions.
- Fallback: if a model or protocol is unavailable, move the task—not the whole development environment—to another compatible route.
Keep the policy in a small project file so the team can revise it:
routes:
architecture:
protocol: claude-messages
model: <verified-model-id>
implementation:
protocol: openai-chat-completions
model: <verified-model-id>
review:
protocol: openai-responses
model: <verified-model-id>
This is intentionally a policy example, not a claim that those three routes accept the same model. Resolve each placeholder from the live catalog and the corresponding client guide.
Validate before enabling agent mode
Do not begin with a large autonomous refactor. Use a staged check:
-
Authentication: request
/v1/modelsand confirm that the token is accepted. - Protocol: send one minimal prompt through the exact endpoint used by the client.
- Model ID: verify that the chosen ID is accepted under the credential's API scope.
- Client: ask the agent to explain one small file without editing it.
- Tool permissions: allow a harmless change on a temporary branch, then inspect the diff.
- Metering: review Credits after a representative task, not after an artificially tiny “hello” request.
A successful directory request alone does not prove that a particular model-client pair will work. If the client still contacts its original provider, verify that you edited the configuration for the same OS user and workspace, then fully restart it. For an unavailable model, refresh /v1/models and compare the ID exactly. For a rejected token, confirm that it belongs to the Coding Application and that its allowed API IDs include the intended endpoint.
Choose a tier from measured work
All four current tiers advertise the same Coding model access; they differ mainly in term quota. Coding Plus targets occasional work, while larger tiers target daily development, sustained agents, or team automation. Credits meter uncached input, output, cache writes, and cache reads separately, so a Credit balance cannot honestly be converted into a fixed number of prompts.
Run three representative jobs—a test-writing task, a cross-file bug investigation, and a code review—and record the Credits consumed. Use that result to choose the next tier. Renewing before expiration carries remaining Credits forward and extends the term by 30 days; otherwise unused Credits expire. There is no auto-renewal according to the current plan disclosure.
The main value is operational: one bounded API budget can support several model families while developers keep familiar clients. The trade-off is that you must manage protocol compatibility, dynamic model IDs, permissions, and Credit consumption explicitly. That is more setup than a single-vendor membership, but it also makes model routing a controllable engineering decision rather than a collection of disconnected subscriptions.
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