Chinese Llm Router

---
name: Chinese LLM Router
description: Route your OpenClaw conversations to the best Chinese AI models —
  no config headaches, just pick and chat.
---

# Chinese LLM Router

Route your OpenClaw conversations to the best Chinese AI models — no config headaches, just pick and chat.

## What It Does

Gives your OpenClaw instant access to all major Chinese LLMs through a single unified interface:

- **DeepSeek** (V3.2 / R1) — Best open-source reasoning, dirt cheap
- **Qwen** (Qwen3-Max / Qwen3-Max-Thinking / Qwen3-Coder-Plus) — Alibaba's flagship, strong all-rounder
- **GLM** (GLM-5 / GLM-4.7) — Zhipu AI, top-tier coding & agent tasks
- **Kimi** (K2.5 / K2.5-Thinking) — Moonshot AI, great for long context & vision
- **Doubao Seed 2.0** (Pro / Lite / Mini) — ByteDance, fast & cheap
- **MiniMax** (M2.5) — Lightweight powerhouse, runs locally too
- **Step** (3.5 Flash) — StepFun, blazing fast inference
- **Baichuan** (Baichuan4-Turbo) — Strong Chinese language understanding
- **Spark** (v4.0 Ultra) — iFlytek, speech & Chinese NLP specialist
- **Hunyuan** (Turbo-S) — Tencent, WeChat ecosystem integration

## Quick Start

Tell your OpenClaw:

```
Use DeepSeek V3.2 for this conversation
```

Or ask it to pick the best model:

```
Which Chinese model is best for coding? Switch to it.
```

## Commands

| Command | What it does |
|---------|-------------|
| `list models` | Show all available Chinese LLMs with status |
| `use <model>` | Switch to a specific model |
| `compare <models>` | Compare capabilities & pricing |
| `recommend <task>` | Get model recommendation for a task type |
| `test <model>` | Send a test prompt to verify connectivity |
| `status` | Check which models are currently accessible |

## Model Selection Guide

| Task | Recommended Model | Why |
|------|------------------|-----|
| General chat | Qwen3-Max | Best all-rounder, strong Chinese |
| Coding | GLM-5 / Kimi K2.5 | Top coding benchmarks |
| Math & reasoning | DeepSeek R1 | Purpose-built for reasoning |
| Long documents | Kimi K2.5 (128K) / DeepSeek V3.2 (1M) | Massive context windows |
| Fast & cheap | Step 3.5 Flash / Doubao Seed 2.0 Mini | Sub-second latency |
| Creative writing | Qwen3-Max / Doubao Seed 2.0 Pro | Rich Chinese expression |
| Agent tasks | GLM-5 / Qwen3-Max | Best tool-use support |

## Configuration

The skill reads API keys from environment or from `~/.chinese-llm-router/config.json`:

```json
{
  "providers": {
    "deepseek": {
      "apiKey": "sk-xxx",
      "baseUrl": "https://api.deepseek.com/v1",
      "models": ["deepseek-chat", "deepseek-reasoner"]
    },
    "qwen": {
      "apiKey": "sk-xxx",
      "baseUrl": "https://dashscope.aliyuncs.com/compatible-mode/v1",
      "models": ["qwen3-max", "qwen3-max-thinking", "qwen3-coder-plus"]
    },
    "glm": {
      "apiKey": "xxx.xxx",
      "baseUrl": "https://open.bigmodel.cn/api/paas/v4",
      "models": ["glm-5", "glm-4-plus"]
    },
    "kimi": {
      "apiKey": "sk-xxx",
      "baseUrl": "https://api.moonshot.cn/v1",
      "models": ["kimi-k2.5", "kimi-k2.5-thinking"]
    },
    "doubao": {
      "apiKey": "xxx",
      "baseUrl": "https://ark.cn-beijing.volces.com/api/v3",
      "models": ["doubao-seed-2.0-pro", "doubao-seed-2.0-lite", "doubao-seed-2.0-mini"]
    },
    "minimax": {
      "apiKey": "xxx",
      "baseUrl": "https://api.minimax.chat/v1",
      "models": ["minimax-m2.5"]
    },
    "step": {
      "apiKey": "xxx",
      "baseUrl": "https://api.stepfun.com/v1",
      "models": ["step-3.5-flash"]
    },
    "baichuan": {
      "apiKey": "xxx",
      "baseUrl": "https://api.baichuan-ai.com/v1",
      "models": ["baichuan4-turbo"]
    },
    "spark": {
      "apiKey": "xxx",
      "baseUrl": "https://spark-api-open.xf-yun.com/v1",
      "models": ["spark-v4.0-ultra"]
    },
    "hunyuan": {
      "apiKey": "xxx",
      "baseUrl": "https://api.hunyuan.cloud.tencent.com/v1",
      "models": ["hunyuan-turbo-s"]
    }
  },
  "default": "qwen3-max",
  "fallback": ["deepseek-chat", "doubao-seed-2.0-pro"]
}
```

## Setup

1. Get API keys from the providers you want (most offer free tiers):
   - DeepSeek: https://platform.deepseek.com
   - Qwen (Alibaba): https://dashscope.console.aliyun.com
   - GLM (Zhipu): https://open.bigmodel.cn
   - Kimi (Moonshot): https://platform.moonshot.cn
   - Doubao (ByteDance): https://console.volcengine.com/ark
   - MiniMax: https://platform.minimaxi.com
   - Step (StepFun): https://platform.stepfun.com
   - Baichuan: https://platform.baichuan-ai.com
   - Spark (iFlytek): https://console.xfyun.cn
   - Hunyuan (Tencent): https://cloud.tencent.com/product/hunyuan

2. Run the setup script:
   ```bash
   node scripts/setup.js
   ```

3. Done! Your OpenClaw can now use any configured model.

## Pricing Reference (Feb 2026)

| Model | Input (¥/M tokens) | Output (¥/M tokens) | Notes |
|-------|-------------------|---------------------|-------|
| DeepSeek V3.2 | ¥0.5 (cache ¥0.1) | ¥2.0 | Cheapest flagship |
| Qwen3-Max | ¥2.0 | ¥6.0 | Free tier available |
| GLM-5 | ¥5.0 | ¥5.0 | Just launched, may change |
| Kimi K2.5 | ¥2.0 | ¥6.0 | Open source, self-host free |
| Doubao Seed 2.0 Pro | ¥0.8 | ¥2.0 | ByteDance subsidy |
| Doubao Seed 2.0 Mini | ¥0.15 | ¥0.3 | Ultra cheap |
| MiniMax M2.5 | ¥1.0 | ¥3.0 | Can run locally |
| Step 3.5 Flash | ¥0.7 | ¥1.4 | Fastest inference |

*Prices as of Feb 2026. All providers offer free tiers or credits for new users.*

## All APIs are OpenAI-Compatible

Every provider listed uses the OpenAI chat/completions format. No special SDKs needed — just change `baseUrl` and `apiKey`.

## Features

- **Auto-fallback**: If one provider is down, automatically try the next
- **Cost tracking**: See per-model token usage and estimated cost
- **Smart routing**: Describe your task, get the best model recommendation
- **Batch compare**: Send the same prompt to multiple models, compare outputs
- **Context-aware**: Remembers your model preference per conversation topic

## Links

- 🦐 Try our AI Plaza: https://ai.xudd-v.com
- 📦 ClawHub: https://clawhub.ai/Xdd-xund/chinese-llm-router
- 💬 Feedback: https://ai.xudd-v.com/connect.html