davinci-002 vs DeepSeek R1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | davinci-002 | DeepSeek R1 |
|---|---|---|
| Provider | OpenAI | DeepSeek |
| Input Price (1M) | $2.00 | $0.28 |
| Output Price (1M) | $2.00 | $0.42 |
| Context Window | 16,384 | 64,000 |
Verdict
davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. DeepSeek R1 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens. DeepSeek R1 is 86% cheaper on input tokens than davinci-002. For output tokens, DeepSeek R1 is the more affordable option at $0.42/1M vs $2.00.
On context window, DeepSeek R1 supports 64,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose davinci-002
- ✓ You are already integrated with OpenAI
When to choose DeepSeek R1
- ✓ You need the lowest input token cost ($ 0.28/1M)
- ✓ Your workload is output-heavy — DeepSeek R1 generates text cheaper
- ✓ You need a larger context window (64,000 tokens)
- ✓ You are already integrated with DeepSeek
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 davinci-002 cheaper than DeepSeek R1? ▼
DeepSeek R1 is cheaper on input tokens at $0.28/1M vs $2.00/1M for davinci-002 — a 86% saving.
What is the context window of davinci-002 vs DeepSeek R1? ▼
davinci-002 has a 16,384-token context window. DeepSeek R1 has a 64,000-token context window. DeepSeek R1 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: davinci-002 or DeepSeek R1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, DeepSeek R1 is the cheaper option. For maximum context length, DeepSeek R1 supports 64,000 tokens. Use the comparison table above to find the right fit for your workload.