Best Chinese AI Model for Your Use Case: A Decision Framework
Coding? Use DeepSeek V3.2. Long documents? Qwen3.5-Plus. Zero budget? GLM-4.7-Flash. Here's how to pick the right Chinese LLM for every scenario.
There are 24+ Chinese LLM APIs available to international developers right now. DeepSeek alone has five variants. Qwen has seven. Picking the wrong one means overpaying 10x or getting 30% worse output.
This framework cuts through the noise. One question at a time, you’ll land on the right model.
The Quick Decision Tree
What's your priority?
├── Lowest cost possible
│ ├── Can tolerate lower quality → Qwen3.5-Flash ($0.028/M input)
│ └── Need zero cost → GLM-4.7-Flash (free)
├── Best coding performance
│ ├── Daily coding assistant → DeepSeek V3.2 ($0.28/M)
│ ├── Hard algorithms → DeepSeek R1 ($0.55/M)
│ └── Near-Opus quality → GLM-5 ($1.00/M)
├── Longest context
│ └── 1M tokens → Qwen3.5-Plus ($0.11/M)
├── Agent / tool-use workflows
│ └── Kimi K2.5 ($0.60/M) — Agent Swarm
├── Deep reasoning (math/science)
│ ├── Budget → DeepSeek R1 ($0.55/M)
│ └── Premium → Qwen3-Max Thinking ($0.34/M)
└── Easiest international access
└── DeepSeek (email signup, credit card, 5 minutes)By Use Case
Coding Assistant (Cursor / Cline)
| Model | Why | Monthly Cost (10M tokens) |
|---|---|---|
| DeepSeek V3.2 | Best price/performance for Python/JS. Full code output, no lazy placeholders. | ~$3.50 |
| GLM-5 | Near-Opus coding at $1/M. Best if quality matters more than cost. | ~$10 |
| Qwen3.5-Flash | Cheapest option that still works. Good for boilerplate and tests. | ~$0.40 |
DeepSeek V3.2 is the default recommendation. Python/JS accuracy at 83-87%, complete code blocks, and caching drops repeated prompts to $0.028/M. Set it up in 30 seconds.
Switch to GLM-5 if you’re writing Rust, C++, or doing complex multi-file refactors where DeepSeek’s 73% SWE-bench score isn’t enough.
Document Processing / RAG
| Model | Why | Context |
|---|---|---|
| Qwen3.5-Plus | 1M context, $0.11/M input. Process entire codebases or long documents in one call. | 1M |
| Kimi K2.5 | 256K context with 75% auto-caching. Great if you’re repeatedly processing similar documents. | 256K |
| Qwen3.5-Flash | If your documents fit in 1M context and you want the absolute cheapest option. $0.028/M input. | 1M |
For RAG pipelines processing thousands of documents: Qwen3.5-Flash at $0.028/M input makes it economically viable to embed and query massive corpora. A million-token document costs $0.028 to process.
Complex Reasoning (Math / Science / Analysis)
| Model | Why | Key Benchmark |
|---|---|---|
| DeepSeek R1 | 97.3% MATH-500. Transparent chain-of-thought. Shows its work. | MATH-500: 97.3% |
| Qwen3-Max Thinking | 1M context + reasoning. For problems that need both deep thinking and lots of context. | MATH-500: ~95% |
R1 is the default for reasoning tasks. But remember: it uses 3-10x more tokens than a general model because of chain-of-thought. For simple math, V3.2 is cheaper and faster.
Agent Workflows
| Model | Why |
|---|---|
| Kimi K2.5 | Agent Swarm: orchestrate up to 100 specialized agents. Auto-caching saves 75% on repeated agent calls. |
| GLM-5 | Best function-calling and structured output among Chinese models. |
| DeepSeek V3.2 | Cheapest option with function-calling support. |
Kimi K2.5’s Agent Swarm is unique — no other Chinese model offers coordinated multi-agent orchestration as a built-in feature. If you’re building complex agent pipelines, it’s worth testing.
Prototyping / Experimentation
| Model | Why |
|---|---|
| GLM-4.7-Flash | Free. 128K context. No credit card. No daily limits. |
| Qwen3.5-Flash | $0.028/M if you need more quality than free. Still nearly free. |
Start with GLM-4.7-Flash for prototyping. When you’re ready for production quality, upgrade to a paid model. Compare costs for your workload.
Multimodal (Image + Text)
| Model | Why |
|---|---|
| Qwen3.5-Plus | Native multimodal (text + image + video). 1M context. |
| Kimi K2.5 | Multimodal with strong visual coding capabilities. |
| Qwen3-VL 235B | Dedicated vision-language model with thinking mode. |
Qwen3.5-Plus is the most capable multimodal Chinese model available via API. If you specifically need vision tasks, Qwen3-VL is the specialist.
The Pricing Landscape
Sorted cheapest to most expensive (input price per 1M tokens):
| Tier | Models | Input Price |
|---|---|---|
| Free | GLM-4.7-Flash | $0 |
| Ultra-cheap | Qwen3.5-Flash, Qwen3-Turbo | $0.007-0.028 |
| Budget | Qwen3-Plus, Step 3.5 Flash | $0.07-0.10 |
| Value | DeepSeek V3.2, Qwen3.5-Plus, MiniMax M2.5 | $0.11-0.30 |
| Mid-range | Qwen3-Max, DeepSeek R1, Kimi K2.5 | $0.34-0.60 |
| Premium | GLM-5, GLM-5-Code, ERNIE 5.0 | $0.83-1.20 |
For comparison, GPT-5.2 is $1.75/M input and Claude Sonnet 4.6 is $3.00/M input. Even the most expensive Chinese model (GLM-5-Code at $1.20) is cheaper than any Western flagship.
Full pricing table: /pricing. Interactive calculator: /calculator.
Access Difficulty
| Difficulty | Providers | What You Need |
|---|---|---|
| Easy (5 min) | DeepSeek, Qwen, GLM (z.ai), StepFun | Email + credit card |
| Moderate | Kimi, MiniMax | Email/phone + credit card. MiniMax needs 2-3 day approval. |
| Difficult | Baidu, ByteDance | Chinese phone number or identity verification. Use OpenRouter instead. |
Step-by-step setup for every provider: complete guide.
The One-Sentence Cheat Sheet
- Default choice: DeepSeek V3.2 — it’s the Honda Civic of Chinese LLMs. Reliable, cheap, good enough for 80% of tasks.
- When you need more: GLM-5 for coding quality, Qwen3.5-Plus for context length, R1 for reasoning.
- When you need less (cost): Qwen3.5-Flash or GLM-4.7-Flash.
- When you need something different: Kimi K2.5 for agents, Qwen3-VL for vision.
Browse all models with detailed specs: Model Directory.