Conclusion
- Cursor/custom-model traffic should be measured by accepted patches and completed tasks.
- DeepSeek and Qwen are common low-cost coding first tests; GLM is useful as domestic fallback.
- OpenAI-compatible settings reduce tool migration friction, but streaming and tool behavior still need smoke tests.
- Budget caps are mandatory before autonomous edit loops or large repo indexing.
What to do next
- Confirm your editor supports custom base_url, api_key, and model settings.
- Run the same three tasks across providers: explain a file, edit one file, fix one failing test.
- Measure accepted patch rate, retries, latency, and token spend.
- Set daily/monthly limits before using long-running agent modes.
- Use OpenLLMAPI when one key, provider routing, logs, and fallback matter more than hand-editing every profile.
Recommended paths
| Provider | Free / credits | Best for |
|---|---|---|
| DeepSeek | Credits/pricing vary | Low-cost reasoning and code edits |
| Qwen | Signup credits vary | Coding, long context, China-friendly setup |
| Zhipu GLM | Signup tokens vary | Domestic GLM fallback and budget tests |
| SiliconFlow | Free/open routes vary | China-direct compatible endpoint experiments |
| OpenLLMAPI | Trial varies | One coding-agent endpoint with budgets and fallback |
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
One budgeted key for coding tools
Route Cursor-style coding tasks across Qwen, DeepSeek, GLM, and fallback models while tracking spend per task or user.
FAQ
Is the cheapest token price best for Cursor?
No. Coding agents can retry, produce failed patches, or hit context limits. Compare cost per accepted code change.
Can I use the same OpenAI SDK-style endpoint?
Usually yes if the provider supports a compatible endpoint, but configure base_url and model explicitly.
Which provider should I test first?
Test DeepSeek and Qwen first for low-cost coding, then GLM/SiliconFlow for China-friendly fallback.
When does a gateway help?
When you manage multiple editors, teams, budgets, providers, or fallback rules and need logs for every agent run.