Mistral: Mistral Small 3.2 24B
Mistral Small 3.2 24B is an affordable, multimodal-capable model with vision support and tool use, making it accessible for lighter content and instruction-following tasks. However, its benchmark scores are modest across reasoning and coding, positioning it as a budget option rather than a primary business workhorse.
Assessment date: March 14, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
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 WildBench and Arena Hard, reduces infinite generations, and delivers gains in tool use and structured output tasks. It supports image and text inputs with structured outputs, function/tool calling, and strong performance across coding (HumanEval+, MBPP), STEM (MMLU, MATH, GPQA), and vision benchmarks (ChartQA, DocVQA).
Capabilities
Architecture
| Modality | Text + Image → Text |
| Tokenizer | Mistral |
| Parameters | 24B |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Evaluations
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.06 | $0.000060 |
| Output | $0.18 | $0.000180 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
