Conclusion
- Best first pick for coding breadth: Qwen, especially if your tool accepts an OpenAI-compatible base_url.
- Best budget/domestic fallback: GLM, when the model you need is available and your key has permission.
- Do not choose only by token price; coding agents need tool-call reliability, context length, retry behavior, and spend caps.
- The safest production path is Qwen primary + GLM/DeepSeek fallback with per-task cost logs.
What to do next
- Confirm your client supports custom base_url, api_key, and model name.
- Smoke-test Qwen compatible mode with a small code-edit prompt and JSON/tool-call requirement.
- Smoke-test GLM with the exact model name and endpoint from the Zhipu console/docs.
- Record pass rate, retries, latency, and cost per successful coding task — not just per-token price.
- Add fallback routing and monthly budget alerts before running long coding-agent sessions.
Recommended paths
| Provider | Free / credits | Best for |
|---|---|---|
| Qwen | Alibaba/DashScope credits vary by account and campaign | Coding breadth, Qwen Coder-family tests, China-friendly setup |
| Zhipu GLM | Signup/Flash routes vary; verify in console | Budget domestic fallback and GLM coding experiments |
| DeepSeek | Free-credit status changes; pricing is the main draw | Low-cost reasoning/coding fallback |
| OpenRouter | Free models are rate-limited | Multi-model comparison before direct-provider setup |
Global developer checklist
- Confirm whether signup, billing, and API keys work from your country before writing production code.
- Prefer OpenAI-compatible endpoints when you may need to switch models, regions, or providers later.
- Test free credits with a real smoke prompt and record latency, error shape, streaming behavior, and quota burn.
- Keep at least one fallback route for provider outages, model deprecations, and regional access changes.
Production handoff
Need one key for Qwen, GLM, and fallbacks?
Use yangmao.ai to compare China-friendly API routes, keep an OpenAI-compatible setup, and add budget-aware fallback before agent runs.
FAQ
Can Qwen and GLM use the OpenAI SDK?
Both have compatible-client patterns, but you must set the provider base_url, key, and exact model name. Do not assume every OpenAI feature is supported identically.
Which is cheaper for coding agents?
It depends on retries and task success. A cheaper model that fails edits twice can cost more than a slightly pricier model that completes the task once.
Which is better for Claude Code-style workflows in China?
Qwen is usually the first test because of coding-model breadth; GLM is a strong fallback if your tool and model permissions are configured correctly.
What should I monitor?
Track tokens, retries, failed tool calls, wall-clock latency, and cost per completed issue or agent run.