Shortlist by task
Start with structured output, coding, extraction, reasoning, or agent execution requirements rather than a generic leaderboard position.
Chinese LLM models list
Compare DeepSeek, Qwen, Kimi, GLM, MiniMax and MiMo routes
Use this model directory to choose Chinese LLM API routes by benchmark score, provider, API model name, and production caveats.
15 documented routes
Model directory
| Model | Provider | Score | Best for |
|---|---|---|---|
Qwen 3.7 Plusqwen3.7-plus | Qwen | 90 Excellent | Structured output, Data extraction, Tool calling |
GLM 5.2glm-5.2 | GLM | 90 Excellent | Structured output, Data extraction, Tool calling |
MiMo v2.5 Promimo-v2.5-pro | MiMo | 90 Excellent | Tool calling, Structured output, Reasoning |
DeepSeek v4 Prodeepseek-v4-pro | DeepSeek | 89 Strong | Tool calling, Instruction following, Structured output |
Qwen 3.6 Plusqwen3.6-plus | Qwen | 89 Strong | Instruction following, Structured output, Data extraction |
Kimi K2.6kimi-k2.6 | Kimi | 88 Strong | Coding support, Instruction following, Structured output |
DeepSeek v4 Flashdeepseek-v4-flash | DeepSeek | 87 Strong | Fallback routing, Cost testing, Instruction following |
GLM 5.1glm-5.1 | GLM | 87 Strong | Tool calling, Structured output, Instruction following |
Kimi K2.5kimi-k2.5 | Kimi | 87 Strong | Fallback routing, Instruction following, Reasoning checks |
GLM 5glm-5 | GLM | 86 Strong | GLM comparison, Structured output testing, Fallback routing |
MiMo v2.5mimo-v2.5 | MiMo | 86 Strong | MiMo comparison, Cost testing, Structured output |
Qwen 3.7 Maxqwen3.7-max | Qwen | 84 Strong | Structured output, Qwen variant testing, Data extraction |
MiniMax M2.7minimax-m2.7 | MiniMax | 83 Strong | MiniMax comparison, Structured output, Fallback routing |
MiniMax M2.5minimax-m2.5 | MiniMax | 81 Strong | Fallback routing, MiniMax comparison, Structured output tests |
MiniMax M3minimax-m3 | MiniMax | 76 Usable | Targeted comparison, Fallback experiments, Non-critical workloads |
Selection workflow
How to choose a Chinese LLM route
Run production prompts
Benchmark scores screen candidates, but your own prompts reveal latency, refusal behavior, tool-call reliability, and cost per solved task.
Keep fallback routes
Chinese LLM providers can differ in availability, policy, context behavior, and price. Keep at least one tested fallback model.
FAQ
Questions developers ask before buying Chinese LLM tokens
Is GPTokens run by a model provider?
No. GPTokens is an independent OpenAI-compatible gateway. It issues GPTokens API keys and routes requests to supported Chinese LLM providers through one account.
Can I use an OpenAI SDK?
Yes. Most integrations only need the GPTokens base URL, a GPTokens API key, and a supported model name from the live model list.
Who is this for?
GPTokens is built for developers and teams in the US, Europe, and other global markets that want to test Chinese LLM APIs without managing separate provider accounts, payment methods, and dashboards.
Should I hard-code model names?
Use the model pages for planning, then call /v1/models before production. Availability, routing, context windows, and price can change as providers update models.