GPT-5.2 vs Mistral Small 3

Detailed pricing comparison and cost analysis.

Updated April 2026

Cost Simulator

GPT-5.2 Cost
$4.55
Mistral Small 3 Cost
$0.05
Mistral Small 3 is 99% cheaper
FeatureGPT-5.2Mistral Small 3
ProviderOpenAIMistral
Input Price (1M)$1.75$0.03
Output Price (1M)$14.00$0.11
Context Window128,00033,000

Verdict

GPT-5.2 costs $1.75 per 1M input tokens and $14.00 per 1M output tokens. Mistral Small 3 costs $0.03 per 1M input tokens and $0.11 per 1M output tokens. Mistral Small 3 is 98% cheaper on input tokens than GPT-5.2. For output tokens, Mistral Small 3 is the more affordable option at $0.11/1M vs $14.00.

On context window, GPT-5.2 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 GPT-5.2

  • ✓ You need a larger context window (128,000 tokens)
  • ✓ You are already integrated with OpenAI

When to choose Mistral Small 3

  • ✓ You need the lowest input token cost ($ 0.03/1M)
  • ✓ Your workload is output-heavy — Mistral Small 3 generates text cheaper
  • ✓ You are already integrated with Mistral

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 GPT-5.2 cheaper than Mistral Small 3?

Mistral Small 3 is cheaper on input tokens at $0.03/1M vs $1.75/1M for GPT-5.2 — a 98% saving.

What is the context window of GPT-5.2 vs Mistral Small 3?

GPT-5.2 has a 128,000-token context window. Mistral Small 3 has a 33,000-token context window. GPT-5.2 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: GPT-5.2 or Mistral Small 3?

The best choice depends on your use case. For cost efficiency on input tokens, Mistral Small 3 is the cheaper option. For maximum context length, GPT-5.2 supports 128,000 tokens. Use the comparison table above to find the right fit for your workload.