davinci-002 vs DeepSeek V3.2
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | davinci-002 | DeepSeek V3.2 |
|---|---|---|
| Provider | OpenAI | DeepSeek |
| Input Price (1M) | $2.00 | $0.28 |
| Output Price (1M) | $2.00 | $0.42 |
| Context Window | 16,384 | 128,000 |
Verdict
davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. DeepSeek V3.2 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens. DeepSeek V3.2 is 86% cheaper on input tokens than davinci-002. For output tokens, DeepSeek V3.2 is the more affordable option at $0.42/1M vs $2.00.
On context window, DeepSeek V3.2 supports 128,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose davinci-002
- ✓ You are already integrated with OpenAI
When to choose DeepSeek V3.2
- ✓ You need the lowest input token cost ($ 0.28/1M)
- ✓ Your workload is output-heavy — DeepSeek V3.2 generates text cheaper
- ✓ You need a larger context window (128,000 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 V3.2? ▼
DeepSeek V3.2 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 V3.2? ▼
davinci-002 has a 16,384-token context window. DeepSeek V3.2 has a 128,000-token context window. DeepSeek V3.2 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: davinci-002 or DeepSeek V3.2? ▼
The best choice depends on your use case. For cost efficiency on input tokens, DeepSeek V3.2 is the cheaper option. For maximum context length, DeepSeek V3.2 supports 128,000 tokens. Use the comparison table above to find the right fit for your workload.