Mistral AI
Codestral-22B-v0.1 is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash (more details in the Blogpost).
29.1
Quality Score
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Arena ELO
22B
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
16 of 22 public signals
Use this section to answer one simple question first: how much outside evidence do we have that this model performs well? Structured benchmark scores appear first, then official provider evidence, then live arena signal.
This model has normalized benchmark rows, so scores here are directly comparable across benchmark sources.
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14.9K
Downloads
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May 2024
Released
4/5 signals
3/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
22B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
These are recent benchmark or leaderboard claims from official provider sources. They are useful for freshness and context, but they are not treated the same as normalized independent benchmark rows.
Codestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View sourceCodestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View sourceCodestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View sourceCodestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View sourceCodestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View sourceCodestral-22B-v0.1 — BigCodeBench #17
Complete: 52.5 | Instruct: 41.8 | 22B params
View source