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Mistral Medium 3 vs babbage-002

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Mistral Medium 3 Cost
$0.80
babbage-002 Cost
$0.48
babbage-002 is 40% cheaper
FeatureMistral Medium 3babbage-002
ProviderMistralOpenAI
Input Price (1M)$0.40$0.40
Output Price (1M)$2.00$0.40
Context Window131,00016,384

Verdict

Mistral Medium 3 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens. babbage-002 costs $0.40 per 1M input tokens and $0.40 per 1M output tokens. Mistral Medium 3 and babbage-002 have identical input token pricing. For output tokens, babbage-002 is the more affordable option at $0.40/1M vs $2.00.

On context window, Mistral Medium 3 supports 131,000 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 Mistral Medium 3

  • ✓ You need a larger context window (131,000 tokens)
  • ✓ You are already integrated with Mistral

When to choose babbage-002

  • ✓ Your workload is output-heavy — babbage-002 generates text cheaper
  • ✓ 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 Mistral Medium 3 cheaper than babbage-002?

Mistral Medium 3 and babbage-002 have identical input token pricing at $0.40/1M tokens.

What is the context window of Mistral Medium 3 vs babbage-002?

Mistral Medium 3 has a 131,000-token context window. babbage-002 has a 16,384-token context window. Mistral Medium 3 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Mistral Medium 3 or babbage-002?

The best choice depends on your use case. For cost efficiency on input tokens, Mistral Medium 3 is the cheaper option. For maximum context length, Mistral Medium 3 supports 131,000 tokens. Use the comparison table above to find the right fit for your workload.