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Mini toolsMistral models
Browse all models from this model family.
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By Mistral AI4B-parameter multilingual streaming ASR model for real-time transcription and translation across 13 languages, delivering sub-500 ms latency with open weights suitable for on-device or server use.NewAudioReleased 13d ago
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By Mistral AIThe largest Ministral 3 model offers frontier text and vision capabilities comparable to larger 24B models. Edge-optimized for single GPU deployment (24GB VRAM in FP8), it delivers state-of-the-art performance for chat, document analysis, and complex reasoning tasks with multilingual support across 40+ languages.NewTextReleased 2mo ago
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By Mistral AIBest-in-class text and vision model for edge deployment, optimized for single GPU operation with minimal footprint. Features interleaved sliding-window attention for efficient inference. Ideal for constrained environments, chat interfaces, image/document understanding, and balanced local deployment scenarios.NewTextReleased 2mo ago
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By Mistral AIThe smallest yet robust Ministral model, edge-optimized for ultra-low-resource environments. Despite its compact size (~3GB), it provides strong language and vision capabilities, outperforming older 7B models. Runs entirely in browser via WebGPU. Ideal for IoT devices, mobile apps, and offline assistants.NewTextReleased 2mo ago
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By Mistral AIMistral 3 is Mistral AI’s next-gen open multimodal, multilingual family, combining small dense Ministral 3 edge models with the frontier Mistral Large 3 MoE to deliver image-aware, long-context language intelligence.NewTextReleased 2mo ago
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By Mistral AIMistral Small 3.1 is a 24B open weights multimodal model with long context, strong coding and reasoning, and efficient deployment on commodity hardware.TextReleased 11mo ago
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By Mistral AIMixtral 8x22B is a sparse mixture-of-experts language model that routes tokens to a subset of experts for high quality reasoning at practical latency.TextReleased 1y ago
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By Mistral AIMistral 3.1 Small is a fast, cost-efficient reasoning model with long context, reliable tool calling, and clean JSON output.TextReleased 11mo ago
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By Mistral AIMagistral Medium 1.2 is Mistral AI’s mid-tier reasoning model, designed to balance capability and efficiency. It delivers stronger analysis, coding, and multilingual performance than the Small variant while keeping inference practical, with support for long-context inputs, JSON outputs, and tool/function calling.TextReleased 4mo ago
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By Mistral AIMagistral Small 1.2 is Mistral AI’s compact reasoning model, optimized for efficiency and cost-sensitive deployments. With strong instruction following, reliable reasoning, and structured JSON outputs, it’s suited for lightweight copilots, chat assistants, and automation workflows where speed and affordability are key.TextReleased 4mo ago
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AudioReleased 7mo ago
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By Mistral AIMistral NeMo is the NVIDIA-optimized deployment of Mistral models, packaged as NeMo/NIM microservices for fast, scalable inference. It brings long-context prompting, tool/function calling, and reliable JSON output with TensorRT-LLM acceleration, quantization, and easy autoscaling on NVIDIA GPUs.TextReleased 1y ago
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By Mistral AIMinistral 8B is Mistral’s compact dense LLM—about 8 billion parameters—built for fast, efficient reasoning, summarization, and coding tasks. It supports long-context prompts, structured JSON outputs, and tool/function calling, making it practical for cost-sensitive copilots and automation.TextReleased 1y ago
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By Mistral AIMinistral 3B (2410) is Mistral’s ultra-compact dense LLM—around 3 billion parameters—built for speed, efficiency, and low compute cost. It supports instruction following, summarization, reasoning, and lightweight coding tasks, with JSON outputs and function/tool calling for agents and automations.TextReleased 1y ago
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By Mistral AIMagistral Medium is Mistral’s mid-tier model in the Magistral line, designed to balance stronger reasoning and coding skills with practical deployment efficiency. It supports long-context prompts, structured JSON outputs, and tool/function calling, making it well suited for enterprise copilots, RAG, and workflow automation.TextReleased 8mo ago
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By Mistral AIMagistral Small is a compact model from Mistral’s specialized lineup, tuned for efficiency while still offering solid reasoning and coding capabilities. At a smaller footprint, it delivers quick instruction following, structured JSON outputs, and function/tool calling support—making it ideal for cost-sensitive, real-time copilots and automations.TextReleased 8mo ago
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TextReleased 8mo ago
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By Mistral AICodestral 25.01 is Mistral’s code-specialized model, tuned for high-quality generation, completion (including fill-in-the-middle), refactoring, debugging, and test creation across popular languages. It handles long-context repos, returns structured outputs, and slots cleanly into IDEs, agents, and CI pipelines.TextReleased 1y ago
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By Mistral AIPixtral 12B is Mistral’s mid-sized vision–language model. It accepts images plus text prompts and generates grounded answers in text, with solid OCR, chart/diagram reasoning, and screenshot/UI understanding. It supports long-context input, function/tool calling, and JSON outputs, balancing quality and efficiency.TextReleased 1y ago
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By Mistral AIPixtral Large is Mistral’s flagship vision-language model. It takes images plus text and returns grounded, step-by-step answers—great for document OCR, charts/diagrams, UI screenshots, and general visual QA—with long-context support, tool/function calling, and reliable JSON outputs.TextReleased 1y ago
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By Mistral AIMistral Small 3.2 (24B) is the largest configuration of the “Small” line—around 24B dense parameters—offering stronger reasoning and coding skills while staying cheaper and faster than Mistral Medium or Large. It supports long context, JSON outputs, and tool/function calling for production copilots and RAG.TextReleased 11mo ago
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