Model Comparison

Codestral-22B vs Gemini 1.5 ProWhich is better in 2026?

Gemini 1.5 Pro significantly outperforms across most benchmarks.

Verdict: Codestral-22B vs Gemini 1.5 Pro — which is better?

Codestral-22B (by Mistral AI) and Gemini 1.5 Pro (by Google) 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.

Codestral-22B outperforms in 0 benchmarks, while Gemini 1.5 Pro is better at 1 benchmark (HumanEval). Gemini 1.5 Pro significantly outperforms across most benchmarks.

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

Choose Gemini 1.5 Pro if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Codestral-22B outperforms in 0 benchmarks, while Gemini 1.5 Pro is better at 1 benchmark (HumanEval).

Gemini 1.5 Pro significantly outperforms across most benchmarks.

Thu Jul 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.5 Pro specifies input context (2,097,152 tokens). Only Gemini 1.5 Pro specifies output context (8,192 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Thu Jul 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 1.5 Pro supports multimodal inputs, whereas Codestral-22B does not.

Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Gemini 1.5 Pro

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Gemini 1.5 Pro uses a proprietary license.

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

Codestral-22B

MNPL-0.1

Open weights

Gemini 1.5 Pro

Proprietary

Closed source

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Gemini 1.5 Pro was released on 2024-05-01.

Codestral-22B is 1 month newer than Gemini 1.5 Pro.

Codestral-22B

May 29, 2024

2.1 years ago

4w newer
Gemini 1.5 Pro

May 1, 2024

2.2 years ago

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Codestral-22B's cutoff date is not specified.

We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

Gemini 1.5 Pro

Nov 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Mistral AI
Has open weights
Google
Larger context window (2,097,152 tokens)
Supports multimodal inputs
Higher HumanEval score (84.1% vs 81.1%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Codestral-22B and Gemini 1.5 Pro side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Gemini 1.5 Pro
Open in Playground
AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
Google
Gemini 1.5 Pro

FAQ

Common questions about Codestral-22B vs Gemini 1.5 Pro.

Which is better, Codestral-22B or Gemini 1.5 Pro?

Gemini 1.5 Pro significantly outperforms across most benchmarks. Codestral-22B is made by Mistral AI and Gemini 1.5 Pro is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Codestral-22B compare to Gemini 1.5 Pro in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%.

What are the context window sizes for Codestral-22B and Gemini 1.5 Pro?

Codestral-22B supports an unknown number of tokens and Gemini 1.5 Pro supports 2.1M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Codestral-22B and Gemini 1.5 Pro?

Key differences include multimodal support (no vs yes), licensing (MNPL-0.1 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Gemini 1.5 Pro?

Codestral-22B is developed by Mistral AI and Gemini 1.5 Pro is developed by Google.

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