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Germey
Germey

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One OpenCode Config for a Multi-Model Coding Budget

#ai #programming #opencode #productivity

If you already use OpenCode and want to assign different coding tasks to different model families without maintaining several client configurations, this guide is for you. AceDataCloud Coding Plan is currently a 30-day, usage-metered API package—not an official Claude, ChatGPT, or other consumer subscription. The current entry tier, Coding Plus, is anchored at ¥99 (the API also lists a USD price of $14.645677) and includes 500 Credits during the current promotion: 400 base plus 100 bonus Credits through November 30, 2026 (UTC+8).

The useful architectural idea is simple: keep one coding client, configure one provider, and choose a model according to the job. The plan currently describes access across Claude, GPT/Codex, GLM, Kimi, and DeepSeek families. Exact model IDs should always come from the live model catalog available to your Coding credential.

Why OpenCode is a practical integration point

The Coding Plan exposes three interface styles:

  • Claude Messages for clients built around Anthropic's Messages protocol.
  • OpenAI Responses for agent workflows such as Codex.
  • OpenAI-compatible Chat Completions for custom-provider clients including OpenCode.

OpenCode uses the third option here. This matters because protocol compatibility and model availability are separate questions. A model family may be in the plan while a particular client still requires a specific adapter or protocol. Do not assume every client supports every model through every interface.

For developers who prefer a terminal workflow, OpenCode provides a useful middle layer: the repository interaction stays the same while the provider configuration identifies the endpoint, credential, and model IDs.

Minimal OpenCode configuration

First, create a Coding application after purchasing a plan and copy its dedicated API key. Use a placeholder while preparing the configuration; never commit the real key.

Install OpenCode using one of its documented methods:

curl -fsSL https://opencode.ai/install | bash
# or
npm install -g opencode-ai
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Export the Coding application key:

export ACEDATACLOUD_API_KEY="YOUR_CODING_APPLICATION_KEY"
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For persistent local use, put that export in your shell profile and protect the file with normal user-only permissions. In CI, use the platform's secret store instead.

Then create or edit ~/.config/opencode/opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "acedatacloud": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ace Data Cloud",
      "options": {
        "baseURL": "https://api.acedata.cloud/v1",
        "apiKey": "{env:ACEDATACLOUD_API_KEY}"
      },
      "models": {
        "MODEL_ID": {
          "name": "MODEL_ID"
        }
      }
    }
  }
}
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Replace both MODEL_ID values with the same live model ID. Use the id returned by the /v1/models response or shown in the current model catalog—not a service UUID and not a marketing display name guessed from a blog post.

The @ai-sdk/openai-compatible adapter is intentional: this OpenCode setup uses the Chat Completions-compatible interface. If your chosen client expects Claude Messages or OpenAI Responses instead, follow that client's guide rather than copying this provider block unchanged.

Verify before giving the agent a repository

Check the setup in increasing order of cost and scope:

opencode auth list
opencode models acedatacloud
opencode run --model acedatacloud/MODEL_ID "Reply only OK"
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These three commands answer different questions:

  1. Is the provider configuration visible?
  2. Can OpenCode discover the configured model?
  3. Can the credential complete a minimal request?

If the model is missing, validate the JSON syntax, file path, environment variable, and exact model ID. A 401 generally points to a missing or invalid key. A quota-related 403 should lead you to the Coding application and plan balance rather than repeated retries.

Only after the minimal request succeeds should you open a real repository. Start with a bounded task such as explaining one module, adding tests around one function, or reviewing a small diff. That makes both output quality and Credit consumption easier to evaluate.

Divide tasks by model role, not brand loyalty

A multi-model plan is most useful when you define a small routing policy before starting work. For example:

  • Use a stronger reasoning model for architecture analysis, cross-file debugging, or a risky refactor.
  • Use a cost-conscious coding model for test generation, repetitive edits, or documentation.
  • Ask a second model family to review a proposed patch when the first answer is plausible but uncertain.

This is a workflow policy, not a claim that one family is always best. Repository size, context length, tool calls, output length, and caching can change both quality and consumption. Keep the task constant when comparing two models, and review the resulting diff and tests rather than judging by prose alone.

To add another model, duplicate the entry under models with another verified ID. Then select it explicitly at run time:

opencode run --model acedatacloud/ANOTHER_MODEL_ID \
  "Review the current diff for correctness and missing tests"
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Explicit selection makes experiments reproducible and helps prevent an expensive model from becoming the accidental default for every small task.

Choose a plan from measured workload

All four current tiers advertise the same Coding model access; they differ mainly in the included Credits. During the promotion ending November 30, 2026 (UTC+8), the public package data lists:

Plan CNY display anchor USD price Promotional Credits Base + bonus
Coding Plus ¥99 $14.645677 500 400 + 100
Coding Standard ¥299 $44.232902 1,600 1,200 + 400
Coding Pro ¥699 $103.407354 4,000 3,000 + 1,000
Coding Max ¥1,399 $206.962643 10,000 8,000 + 2,000

Do not mix the CNY display anchor with the USD price in calculations. Credits are deducted according to usage, and uncached input, output, cache writes, and cache reads are metered separately. Long context, agent loops, and parallel work therefore do not translate into a fixed number of prompts.

The plan does not auto-renew or automatically fall back to a general account balance. Renewal before expiry can carry remaining Credits forward and extend validity by 30 days; unused Credits expire when the term ends if you do not renew in time.

A sensible starting process is to buy the smallest tier that fits your initial project, run three representative tasks, record the Credit cost of each, and project your own 30-day workload. Upgrade based on those measurements—not on a generic “requests per day” estimate.

References and next steps

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