Model Comparison

Gemini 1.0 Pro vs Codestral-22BWhich is better in 2026?

Comparing Gemini 1.0 Pro and Codestral-22B across benchmarks, pricing, and capabilities.

Verdict: Gemini 1.0 Pro vs Codestral-22B — which is better?

Gemini 1.0 Pro (by Google) and Codestral-22B (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose Gemini 1.0 Pro if…

  • you want predictable pricing at $0.50/M input and $1.50/M output

Choose Codestral-22B if…

  • you want the most recent training data — it shipped May 2024
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemini 1.0 Pro and Codestral-22B don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.0 Pro specifies input context (32,760 tokens). Only Gemini 1.0 Pro specifies output context (8,192 tokens).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Sun Jun 07 2026 • llm-stats.com

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Codestral-22B uses MNPL-0.1.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 1.0 Pro

Proprietary

Closed source

Codestral-22B

MNPL-0.1

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Codestral-22B was released on 2024-05-29.

Codestral-22B is 3 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.3 years ago

Codestral-22B

May 29, 2024

2.0 years ago

3mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Codestral-22B's cutoff date is not specified.

We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Codestral-22B's cutoff date.

Gemini 1.0 Pro

Feb 2024

Codestral-22B

—

Outputs Comparison

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Key Takeaways

Google
Larger context window (32,760 tokens)
Mistral AI
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Mistral AI
Codestral-22B

FAQ

Common questions about Gemini 1.0 Pro vs Codestral-22B.

Which is better, Gemini 1.0 Pro or Codestral-22B?

Gemini 1.0 Pro (Google) and Codestral-22B (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 1.0 Pro compare to Codestral-22B in benchmarks?

Gemini 1.0 Pro scores BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%, MMMU: 47.9%. Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%.

What are the context window sizes for Gemini 1.0 Pro and Codestral-22B?

Gemini 1.0 Pro supports 33K tokens and Codestral-22B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.0 Pro and Codestral-22B?

Key differences include licensing (Proprietary vs MNPL-0.1). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.0 Pro and Codestral-22B?

Gemini 1.0 Pro is developed by Google and Codestral-22B is developed by Mistral AI.

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