Conclusion
- Best first free-credit path: Qwen, especially for coding-agent experiments and long context tests.
- Best low-cost paid fallback: DeepSeek, because agent loops can burn output tokens quickly.
- Best fast free smoke test: Groq or NVIDIA NIM when supported model limits fit your workflow.
- Best one-key handoff: an OpenAI-compatible relay when you need GPT/Claude/Gemini plus China-friendly model fallback.
What to do next
- Put base_url, api_key, model, max_tokens, and temperature in OpenClaw config instead of code.
- Run the same 3-task smoke suite: code edit, web summary, and JSON extraction.
- Record latency, streaming behavior, rate-limit errors, and cost per successful task.
- Use free routes only for prototyping; set a paid fallback, budget cap, and idle/heartbeat guard before long autonomous runs.
- Keep model aliases such as fast, cheap, and strong so you can switch providers without rewriting prompts.
Recommended paths
| Provider | Free / credits | Best for |
|---|---|---|
| Qwen | 70M signup tokens | OpenClaw coding-agent tests and China-friendly setup |
| DeepSeek | $5 signup / current credit | Cheap coding, reasoning, and agent loops |
| Groq | Free developer limits vary | Low-latency smoke tests on open models |
| NVIDIA NIM | Free hosted model testing | NIM catalog experiments and Cursor/OpenClaw setup |
| OpenLLMAPI | Signup credit varies | One endpoint for cheap primary + premium 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
Want one OpenClaw key with fallback?
Start on free credits, then run OpenClaw against one compatible endpoint that can route cheap agent steps to Qwen/DeepSeek and fallback to stronger GPT, Claude, or Gemini models.
FAQ
Can OpenClaw use an OpenAI-compatible API?
Yes. The safest setup is to make base_url, api_key, and model configurable, then test streaming, tool calls, JSON output, and retry behavior with your exact OpenClaw workflow.
Which free API should I use first?
Use Qwen when credits and China access matter, Groq or NVIDIA NIM for fast no/low-cost smoke tests, and OpenRouter when you want to try several free models quickly.
Why not run OpenClaw only on free APIs?
Free APIs can have rate limits, model changes, and unavailable routes. Agent loops amplify failures, so production needs at least one paid fallback.
How do I control OpenClaw API cost?
Cap max output tokens, summarize tool results, cache repeated context, route simple steps to cheap models, and reserve premium models for planning or final review.