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davinci-002 vs Qwen3.7-Max

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

davinci-002 Cost
$2.40
Qwen3.7-Max Cost
$2.00
Qwen3.7-Max is 17% cheaper
Featuredavinci-002Qwen3.7-Max
ProviderOpenAIAlibaba
Input Price (1M)$2.00$1.25
Output Price (1M)$2.00$3.75
Context Window16,3841,000,000

Verdict

davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. Qwen3.7-Max costs $1.25 per 1M input tokens and $3.75 per 1M output tokens. Qwen3.7-Max is 38% cheaper on input tokens than davinci-002. For output tokens, davinci-002 is the more affordable option at $2.00/1M vs $3.75.

On context window, Qwen3.7-Max supports 1,000,000 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

  • ✓ Your workload is output-heavy — davinci-002 generates text cheaper
  • ✓ You are already integrated with OpenAI

When to choose Qwen3.7-Max

  • ✓ You need the lowest input token cost ($ 1.25/1M)
  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with Alibaba

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 Qwen3.7-Max?

Qwen3.7-Max is cheaper on input tokens at $1.25/1M vs $2.00/1M for davinci-002 — a 38% saving.

What is the context window of davinci-002 vs Qwen3.7-Max?

davinci-002 has a 16,384-token context window. Qwen3.7-Max has a 1,000,000-token context window. Qwen3.7-Max supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: davinci-002 or Qwen3.7-Max?

The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.7-Max is the cheaper option. For maximum context length, Qwen3.7-Max supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.