DeepSeek API Pricing (Cost Drivers)
How to estimate DeepSeek costs and compare value across tasks, especially when you optimize prompts and reduce retries.
DeepSeek pricing can look great on paper, but cost still depends on token usage, tool chains, and retries.
Where DeepSeek cost comes from
- Input tokens (prompt + context)
- Output tokens (responses)
- Workflow amplification (tools + retries)
DeepSeek vs OpenAI (how to compare fairly)
Don’t compare just “headline rates.” Compare your real workflow: how many calls and how many billed tokens per user action.
What about Qwen and Kimi?
Use the same framework: estimate tokens per request, then multiply by model-specific input/output rates.
Next step
Run a token estimate with the calculators to get a monthly spend picture.
Related reading
A clear way to estimate Claude costs, including input vs output tokens and workflow call volume.
A decision framework for choosing between GPT-4 and Claude based on real workflow token usage.
Understand Kimi pricing with input/output tokens and workflow call volume so you can control spend.
Understand OpenAI cost drivers and how to estimate cost per token for input and output.