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Codestral vs GPT-5.6 Terra

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Codestral Cost
$0.48
GPT-5.6 Terra Cost
$4.40
Codestral is 89% cheaper
FeatureCodestralGPT-5.6 Terra
ProviderMistralOpenAI
Input Price (1M)$0.30$2.00
Output Price (1M)$0.90$12.00
Context Window256,0001,000,000

Verdict

Codestral costs $0.30 per 1M input tokens and $0.90 per 1M output tokens. GPT-5.6 Terra costs $2.00 per 1M input tokens and $12.00 per 1M output tokens. Codestral is 85% cheaper on input tokens than GPT-5.6 Terra. For output tokens, Codestral is the more affordable option at $0.90/1M 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 Codestral

  • ✓ You need the lowest input token cost ($ 0.30/1M)
  • ✓ Your workload is output-heavy — Codestral generates text cheaper
  • ✓ You are already integrated with Mistral

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 Codestral cheaper than GPT-5.6 Terra?

Codestral is cheaper on input tokens at $0.30/1M vs $2.00/1M for GPT-5.6 Terra — a 85% saving.

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

Codestral has a 256,000-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: Codestral or GPT-5.6 Terra?

The best choice depends on your use case. For cost efficiency on input tokens, Codestral 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.