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Codestral-22B vs Gemini 2.0 Flash

Gemini 2.0 Flash leads the LLM Stats Score 16.5 to 0.5.

Mistral AI · Google · Updated for 2026

Which is better?

Gemini 2.0 Flash leads the overall LLM Stats Score 16.5 to 0.5, ranking #203 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Codestral-22B

  • you need open weights you can self-host or fine-tune

Choose Gemini 2.0 Flash

  • overall performance matters — it scores 16.5 and ranks #203 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Dec 2024

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Gemini 2.0 Flash
Google
Core performance indexes
LLM Stats Score
0.5
#304
16.5
#203
Reasoning
0.4
#297
15.9
#202
Coding
2.6
#209
1.7
#212
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.10 / M
Output price
— / M
$0.40 / M
Context window
—
1,048,576

Individual benchmarks

7 reported for Codestral-22B · 13 for Gemini 2.0 Flash

No common benchmarks found

Codestral-22B and Gemini 2.0 Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Gemini 2.0 Flash specifies input context (1,048,576 tokens). Only Gemini 2.0 Flash specifies output context (8,192 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Sun Aug 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 2.0 Flash supports multimodal inputs, whereas Codestral-22B does not.

Gemini 2.0 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Gemini 2.0 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Gemini 2.0 Flash 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 2.0 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Gemini 2.0 Flash was released on 2024-12-01.

Gemini 2.0 Flash is 6 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

Gemini 2.0 Flash

Dec 1, 2024

1.7 years ago

6mo newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a documented knowledge cutoff of 2024-08-01, while Codestral-22B's cutoff date is not specified.

We can confirm Gemini 2.0 Flash's training data extends to 2024-08-01, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

Gemini 2.0 Flash

Aug 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Codestral-22B and Gemini 2.0 Flash side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Gemini 2.0 Flash
Open in Playground

FAQ

Common questions about Codestral-22B vs Gemini 2.0 Flash.

Which is better, Codestral-22B or Gemini 2.0 Flash?

Gemini 2.0 Flash leads the LLM Stats Score 16.5 to 0.5. Codestral-22B is made by Mistral AI and Gemini 2.0 Flash is made by Google. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to Gemini 2.0 Flash in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%.

What are the context window sizes for Codestral-22B and Gemini 2.0 Flash?

Codestral-22B supports an unknown number of tokens and Gemini 2.0 Flash supports 1.0M 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 2.0 Flash?

Key differences include LLM Stats Score (0.5 vs 16.5), 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 2.0 Flash?

Codestral-22B is developed by Mistral AI and Gemini 2.0 Flash is developed by Google.

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