Codestral-22B vs Qwen2.5 7B Instruct Comparison
Comparing Codestral-22B and Qwen2.5 7B Instruct across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Codestral-22B outperforms in 0 benchmarks, while Qwen2.5 7B Instruct is better at 2 benchmarks (HumanEval, MBPP).
Qwen2.5 7B Instruct significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
Codestral-22B has 14.6B more parameters than Qwen2.5 7B Instruct, making it 191.7% larger.
Context Window
Maximum input and output token capacity
Only Qwen2.5 7B Instruct specifies input context (131,072 tokens). Only Qwen2.5 7B Instruct specifies output context (8,192 tokens).
License
Usage and distribution terms
Codestral-22B is licensed under MNPL-0.1, while Qwen2.5 7B 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 7B Instruct was released on 2024-09-19.
Qwen2.5 7B Instruct is 4 months newer than Codestral-22B.
May 29, 2024
1.8 years ago
Sep 19, 2024
1.5 years ago
3mo 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
Qwen2.5 7B Instruct
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
| Feature | | |
|---|