Model Comparison
Codestral-22B vs Qwen2.5 VL 32B Instruct
Qwen2.5 VL 32B Instruct significantly outperforms across most benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
Codestral-22B outperforms in 0 benchmarks, while Qwen2.5 VL 32B Instruct is better at 2 benchmarks (HumanEval, MBPP).
Qwen2.5 VL 32B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Model Size
Parameter count comparison
Qwen2.5 VL 32B Instruct has 11.3B more parameters than Codestral-22B, making it 50.9% larger.
Input Capabilities
Supported data types and modalities
Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas Codestral-22B does not.
Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Codestral-22B
Qwen2.5 VL 32B Instruct
License
Usage and distribution terms
Codestral-22B is licensed under MNPL-0.1, while Qwen2.5 VL 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MNPL-0.1
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Codestral-22B was released on 2024-05-29, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.
Qwen2.5 VL 32B Instruct is 9 months newer than Codestral-22B.
May 29, 2024
2.0 years ago
Feb 28, 2025
1.2 years ago
9mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
Codestral-22B
View detailsMistral AI
No standout differentiators in the data we have for this pair.
Qwen2.5 VL 32B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Codestral-22B vs Qwen2.5 VL 32B Instruct.