Codestral-22B vs DeepSeek-V3
Comparing Codestral-22B by Mistral AI and DeepSeek-V3 by DeepSeek across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
Codestral-22B and DeepSeek-V3 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
DeepSeek-V3 has 648.8B more parameters than Codestral-22B, making it 2922.5% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).
License
Usage and distribution terms
Codestral-22B is licensed under MNPL-0.1, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).
License differences may affect how you can use these models in commercial or open-source projects.
MNPL-0.1
Open weights
MIT + Model License (Commercial use allowed)
Open weights
Release Timeline
When each model was launched
Codestral-22B was released on 2024-05-29, while DeepSeek-V3 was released on 2024-12-25.
DeepSeek-V3 is 7 months newer than Codestral-22B.
May 29, 2024
1.8 years ago
Dec 25, 2024
1.2 years ago
7mo 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
DeepSeek-V3
View detailsDeepSeek
Detailed Comparison
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