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Model details

Mistral Small 3.2 24B

Mistral Small 3.2 24B Instruct is a multimodal model built to balance high-level reasoning capabilities with efficient performance. Designed as an evolution of the 3.1 series, this architecture maintains a 24-billion parameter scale while integrating vision understanding alongside its core text processing. It is specifically engineered to handle complex instruction-following tasks and structured output generation, making it a versatile tool for developers who require reliable, consistent responses across diverse applications ranging from coding assistance to document analysis.

The model benefits from targeted refinements in its post-training process, which significantly improve its ability to adhere to precise instructions and reduce the occurrence of repetitive or infinite text generations. These enhancements extend to its function-calling framework, which is now more robust, allowing for more reliable integration with external tools and APIs. By maintaining strong performance across standard benchmarks like WildBench and Arena Hard, the model serves as a practical, high-utility option for users seeking a balance between depth of reasoning and operational efficiency in real-world deployment scenarios.

OpenRoutermistralai/mistral-small-3.2-24b-instructmistral-small

Quick Info

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Provider
OpenRouter
Model key
mistralai/mistral-small-3.2-24b-instruct
Release date
Jun 20, 2025
Last updated
Jun 20, 2025
Knowledge cutoff
2023-10-31
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.09375
Output token cost
$0.25

Limits

Output tokens
16,384 tokens
Context window
256,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Mistral Small 3.2 24B

OpenRouter

Coverage

The official Mistral AI Hugging Face model card for Mistral-Small-3.2-24B-Instruct-2506 describes it as a minor update over Mistral-Small-3.1-24B-Instruct-2503, with three concrete improvements: better instruction following, a 2x reduction in infinite or repetitive generations (1.29% vs 2.11% internally), and a more ro For deployment, the card recommends vLLM 0.9.1 (which pulls in mistral_common 1.6.2) and also lists a transformers-based usage path, advising a low temperature around 0.15 and including a SYSTEM_PROMPT.txt reference for general-assistant behavior. Key features such as context window, vision capability, and function-cal

OpenRouter

Official sourceBenchmark

Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. $0.15 per million input tokens, $0.60 per million output tokens. 262,144 token context window. Higher uptime with 2 providers. Includes independent benchmarks from Ar

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