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davinci-002 vs GPT-5.6 Terra

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

davinci-002 Cost
$2.40
GPT-5.6 Terra Cost
$4.40
davinci-002 is 45% cheaper
Featuredavinci-002GPT-5.6 Terra
ProviderOpenAIOpenAI
Input Price (1M)$2.00$2.00
Output Price (1M)$2.00$12.00
Context Window16,3841,000,000

Verdict

davinci-002 costs $2.00 per 1M input tokens and $2.00 per 1M output tokens. GPT-5.6 Terra costs $2.00 per 1M input tokens and $12.00 per 1M output tokens. davinci-002 and GPT-5.6 Terra have identical input token pricing. For output tokens, davinci-002 is the more affordable option at $2.00/1M vs $12.00.

On context window, GPT-5.6 Terra 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 GPT-5.6 Terra

  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ 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 davinci-002 cheaper than GPT-5.6 Terra?

davinci-002 and GPT-5.6 Terra have identical input token pricing at $2.00/1M tokens.

What is the context window of davinci-002 vs GPT-5.6 Terra?

davinci-002 has a 16,384-token context window. GPT-5.6 Terra has a 1,000,000-token context window. GPT-5.6 Terra supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: davinci-002 or GPT-5.6 Terra?

The best choice depends on your use case. For cost efficiency on input tokens, davinci-002 is the cheaper option. For maximum context length, GPT-5.6 Terra supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.