Conclusion
- Use official DeepSeek pricing as source of truth.
- Compare cost per successful task, not headline token price.
- Cache-hit discounts help repeated context but not every request.
- Production apps need fallback and budget logs.
What to do next
- Record current pricing, cache, and off-peak rules.
- Run realistic high-volume workflows.
- Measure retries, invalid JSON, latency, and final cost.
- Compare DeepSeek against Qwen, GLM, and fallback.
- Use OpenLLMAPI when you need routing, logs, and caps.
Recommended paths
| Provider | Free / credits | Best for |
|---|---|---|
| DeepSeek | Verify current credits/pricing | Low-cost reasoning and coding |
| Qwen | Signup credits vary | China-friendly compatible setup |
| Zhipu GLM | Signup tokens vary | Domestic fallback |
| OpenLLMAPI | Trial varies | One endpoint with logs 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
Turn cheap DeepSeek calls into a controlled route
Route DeepSeek first, fallback failures, and track spend by app, user, feature, or agent run.
FAQ
Is DeepSeek always cheapest?
No. Retries, cache misses, long outputs, and failed tasks change effective cost.
Where should I verify pricing?
Use official DeepSeek API pricing docs and your account console.
When should I add fallback?
Before user-facing launch or scheduled agents.