Conclusion
- For prototypes, pick the provider that gives a real API key fastest and supports OpenAI-compatible chat completions.
- For long-running OpenClaw agents, cheapest token price is not enough: verify rate limits, reconnect behavior, tool-call support, and failure handling.
- For production, keep provider selection configurable and route risky workloads through a gateway with per-agent budget logs.
What to do next
- List the agent workload: coding, browser automation, email/admin, research, or scheduled monitoring.
- Test one China-friendly compatible model and one global fallback with the same OpenAI SDK client.
- Run a 30-minute loop and record tokens, retries, latency, and failed tool calls.
- Set a hard monthly budget and alerts before leaving any agent unattended.
- Move production traffic behind OpenLLMAPI or another gateway only when fallback and logs are needed.
Recommended paths
| Provider | Free / credits | Best for |
|---|---|---|
| Qwen | Signup credits vary | China-friendly coding and agent tests |
| DeepSeek | Check official pricing/credits | Low-cost reasoning and code tasks |
| Zhipu GLM | Credits vary | Domestic fallback and Claude-Code-style experiments |
| OpenLLMAPI | Trial terms vary | One key, fallback, logs, and routing |
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
Run OpenClaw agents with budget control
Keep the OpenAI-compatible client, add fallback routes, and see per-agent spend before unattended loops get expensive.
FAQ
Can OpenClaw use any OpenAI-compatible API?
Usually yes if the tool lets you set base_url, api_key, and model. Still test streaming, tool calls, and reconnects before trusting autonomous loops.
Should I choose the cheapest model for agents?
Not blindly. Retries, bad tool calls, and context failures can make a cheap model more expensive than a stable route.
When is a gateway worth it?
Use a gateway when multiple agents share keys, you need fallback, or you want per-agent cost attribution and alerts.