Chinese LLM APIs: DeepSeek, Qwen, GLM, Kimi and MiniMax

1. Choose the workload before the model family

“Best Chinese model” is too broad to be an engineering requirement. A code-review service, a Chinese document workflow, a long-context search assistant and a high-volume classification queue have different success criteria. Define the input, required output format, latency tolerance, monthly budget and fallback behavior before comparing names.

The model catalog on island AI Coding changes over time. Treat the models below as families to test, not permanent rankings. The exact ID, context window, tool support, multimodal fields, price and account permission must be copied from the current model page or control panel.

2. A task-first comparison matrix

A family name does not guarantee that every variant supports the same tools, reasoning controls, image fields or context length. Run the API test against the exact model ID you intend to deploy.

3. Test through one OpenAI-compatible request

Start with a minimal request that proves authentication and model permission. Add tools, streaming, images and long context only after the short request succeeds.

curl https://www.codex789.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MODEL_ID_FROM_CONTROL_PANEL",
    "messages": [{"role": "user", "content": "Return only valid JSON: {\"ok\":true}"}],
    "stream": false
  }'

Store the HTTP status, request ID, model ID, input/output token counts and the raw response before a client library transforms it. That record makes it possible to distinguish provider output from SDK parsing or application bugs. When a provider-specific field matters, compare the gateway behavior with the official DeepSeek API documentation or official Qwen documentation.

4. Display names, API IDs and account permissions

A marketing name and an API model ID are not necessarily identical. “Model not found” can mean a spelling error, a retired alias, a model outside the key's group or an account permission that has not been enabled. Do not keep editing the request body until you have copied the current ID from the account surface.

1. Use a project-specific API key rather than a shared personal key.
2. List the model ID, intended workload and fallback in deployment configuration.
3. Run one short non-streaming request.
4. Add streaming and tools as separate tests.
5. Pin a known working fallback ID before increasing traffic.

5. Separate 429, server capacity and balance problems

A 429 response may describe request rate, token rate, concurrency or an account-level limit. A “server busy” or 5xx response may indicate temporary upstream capacity. A payment or balance failure belongs to a different layer. Read the response body and control-panel request record instead of labeling every failure “rate limited.”

6. Production routing without accidental complexity

A stable starting design has one default model per workload and one explicitly tested fallback. Route by a deterministic rule such as task type, required context or output schema. Do not use an LLM to decide routing when ordinary configuration already knows the task.

• Give each environment and application its own key and spend limit.
• Log the requested and actual model IDs.
• Use a retry budget shared across the primary and fallback.
• Record why a fallback happened.
• Do not send tools or image fields to a fallback that has not passed those tests.

7. Compare cost per accepted task

Normalize text pricing to the same token unit, then include input size, output size, reasoning tokens where exposed, caching rules and retries. The lowest catalog multiplier is not necessarily the lowest workflow cost if the model produces more rejected outputs or repeatedly misses the schema.

The current site uses CNY pricing and supports WeChat Pay and Alipay recharge. Some domestic-model channels are displayed with discounted directory multipliers, but the final account ledger is the billing source of truth. Keep the pricing snapshot date with every benchmark.

8. A small benchmark that proves something useful

Create four task groups with at least several representative samples each:

1. Chinese summarization: require named facts, a length limit and a citation field.
2. Code repair: run the patch against tests instead of grading prose.
3. Structured output: validate JSON with a schema and count retries.
4. Long context: plant answerable details across the document and measure missed evidence.

For every model, record task pass/fail, token use, latency, retry count, fallback count and human review time. Select the default only after removing models that fail the required output contract.

9. Frequently asked questions

Can I use the OpenAI SDK with Chinese models?

For models exposed through the site's OpenAI-compatible interface, the common integration changes are the base URL, bearer key and model ID. Native tools, reasoning controls, image fields and streaming details still require model-specific tests.

Should I integrate DeepSeek, Qwen, GLM and Kimi at the same time?

No. Start with one primary and one fallback for a defined workload. Add a third family only when it solves a measured gap.

Does a lower multiplier guarantee a lower production cost?

No. Compare total spend per accepted output, including retries, long outputs and human correction.

Where can I see the available IDs?

Use the current model catalog and the permissions visible for your API key. Do not copy an old blog-post alias into production.

For video generation rather than text models, see the Seedance 2.5 API guide.

Reviewed September 19, 2026. This page provides an evaluation and integration method; it does not claim that one family is universally best or that every listed variant is enabled for every account.