Model Comparison

Codestral-22B vs Qwen2.5-Omni-7BWhich is better in 2026?

Codestral-22B significantly outperforms across most benchmarks.

Verdict: Codestral-22B vs Qwen2.5-Omni-7B — which is better?

Codestral-22B (by Mistral AI) and Qwen2.5-Omni-7B (by Alibaba Cloud / Qwen Team) 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 2 benchmarks (HumanEval, MBPP), while Qwen2.5-Omni-7B is better at 0 benchmarks. Codestral-22B significantly outperforms across most benchmarks.

Choose Codestral-22B if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks

Choose Qwen2.5-Omni-7B if…

  • you want the most recent training data — it shipped Mar 2025
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Codestral-22B outperforms in 2 benchmarks (HumanEval, MBPP), while Qwen2.5-Omni-7B is better at 0 benchmarks.

Codestral-22B significantly outperforms across most benchmarks.

Tue Jun 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

15.2B diff

Codestral-22B has 15.2B more parameters than Qwen2.5-Omni-7B, making it 217.1% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
22.2B
Codestral-22B
7.0B
Qwen2.5-Omni-7B

Input Capabilities

Supported data types and modalities

Qwen2.5-Omni-7B supports multimodal inputs, whereas Codestral-22B does not.

Qwen2.5-Omni-7B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Qwen2.5-Omni-7B uses Apache 2.0.

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

Codestral-22B

MNPL-0.1

Open weights

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 10 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.0 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.2 years ago

10mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Mistral AI
Higher HumanEval score (81.1% vs 78.7%)
Higher MBPP score (78.2% vs 73.2%)
Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about Codestral-22B vs Qwen2.5-Omni-7B.

Which is better, Codestral-22B or Qwen2.5-Omni-7B?

Codestral-22B significantly outperforms across most benchmarks. Codestral-22B is made by Mistral AI and Qwen2.5-Omni-7B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Codestral-22B compare to Qwen2.5-Omni-7B in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Qwen2.5-Omni-7B scores FLEURS: 95.9%, DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%.

What are the main differences between Codestral-22B and Qwen2.5-Omni-7B?

Key differences include multimodal support (no vs yes), licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Qwen2.5-Omni-7B?

Codestral-22B is developed by Mistral AI and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.

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