Mistral: Mistral Small 3.2 24B Rank
Mistral Small 3.2 24B has an overall score of 57 out of 100, tied for rank 226 of 291. The published scores are price 90, context 53, parameters 35, and freshness 48. The overall score is their average. recency is not published and is left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 226 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 48 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 53 | 256K tokens, output 16.4K | AI Context Window |
| Parameters | 35 | 24B total | AI Parameter Count |
| Price | 90 | $0.106 / 1M blended, $0.075 / 1M input, $0.2 / 1M output | AI Token Price |
225 listed models have a higher overall score. Among Mistral models, it ranks 8 of 20.
Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...
Higher overall scores
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Frequently asked questions
What is the Mistral Small 3.2 24B rank?
Mistral Small 3.2 24B has an overall score of 57 out of 100, tied for rank 226 of 291. The published scores are price 90, context 53, parameters 35, and freshness 48. The overall score is their average. recency is not published and is left out of the average.
Where does Mistral Small 3.2 24B rank?
Mistral Small 3.2 24B is tied for rank 226 of 291. 225 listed models have a higher overall score. Among Mistral models, it ranks 8 of 20.
What scores make up Mistral Small 3.2 24B?
Mistral Small 3.2 24B scores price 90 (AI Token Price), context 53 (AI Context Window), parameters 35 (AI Parameter Count), and freshness 48 (AI Knowledge Cutoff). The overall score of 57 is the average of those 4.