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Model details

Mistral Small 3.1 24B

Mistral Small 3.1 24B Instruct is a multimodal 24-billion-parameter model that brings vision understanding and extended context handling to Mistral's compact Small family, building on the lineage from Mistral Small 3 2501. It processes both text and image inputs while producing text output, supporting over 22 languages including English, French, Spanish, German, Chinese, Japanese, and many others. The model achieves around 150 tokens per second in inference, making it fast enough for conversational assistants and interactive applications. It outperforms comparable models like Gemma 3 and GPT-4o Mini, and can run on a single RTX 4090 GPU or a Mac with 32GB RAM, enabling efficient local inference for privacy-sensitive deployments.

This instruction-finetuned variant derives from the Mistral-Small-3.1-24B-Base-2503 base model, adding state-of-the-art vision capabilities alongside the extended context handling without sacrificing performance on standard language tasks. The model is available under Apache 2.0 licensing, making it fully open for commercial use and fine-tuning. Organizations can specialize it for domains like legal advice, medical diagnostics, or technical support through targeted fine-tuning, creating accurate subject matter experts. Its lightweight footprint combined with strong performance in text, code, math, and vision tasks makes it particularly practical for teams that need advanced AI capabilities without relying on cloud services or enterprise budgets.

OpenRoutermistralai/mistral-small-3.1-24b-instructmistral-small

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Provider
OpenRouter
Model key
mistralai/mistral-small-3.1-24b-instruct
Release date
Mar 17, 2025
Last updated
Mar 17, 2025
Knowledge cutoff
2023-10-31
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.351
Output token cost
$0.555

Limits

Output tokens
102,400 tokens
Context window
128,000 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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