o4-mini vs davinci-002
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | o4-mini | davinci-002 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price (1M) | $1.10 | $2.00 |
| Output Price (1M) | $4.40 | $2.00 |
| Context Window | 200,000 | 16,384 |
Verdict
o4-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens. davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. o4-mini is 45% cheaper on input tokens than davinci-002. For output tokens, davinci-002 is the more affordable option at $2.00/1M vs $4.40.
On context window, o4-mini supports 200,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose o4-mini
- ✓ You need the lowest input token cost ($ 1.10/1M)
- ✓ You need a larger context window (200,000 tokens)
- ✓ You are already integrated with OpenAI
When to choose davinci-002
- ✓ Your workload is output-heavy — davinci-002 generates text cheaper
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is o4-mini cheaper than davinci-002? ▼
o4-mini is cheaper on input tokens at $1.10/1M vs $2.00/1M for davinci-002 — a 45% saving.
What is the context window of o4-mini vs davinci-002? ▼
o4-mini has a 200,000-token context window. davinci-002 has a 16,384-token context window. o4-mini supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: o4-mini or davinci-002? ▼
The best choice depends on your use case. For cost efficiency on input tokens, o4-mini is the cheaper option. For maximum context length, o4-mini supports 200,000 tokens. Use the comparison table above to find the right fit for your workload.