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Mistral Large 3

Mistral Large 3

v25.12ย ยทย Family: Mistral
Open-weight multimodal model from Mistral AI (December 2025), built on a Mixture-of-Experts architecture with 41B active and 675B total parameters, 256k context, Apache 2.0 license.
โœ“ Activeโœ“ Public accessโš– Open sourceLLMMultimodal๐Ÿ“ Mistral
Context window
256k
tokens
Parameters
675B total / 41B active
parameters
Release date
2 December 2025
Access:APIDownloadHostedDeployment:โ˜ Cloud๐Ÿ’ป Local

Overview

Mistral Large 3 is a multimodal language model announced by Mistral AI on December 2, 2025, as part of the Mistral 3 family. The model uses a sparse Mixture-of-Experts (MoE) architecture with 41B active and 675B total parameters, and a 256k context window.

It was trained from scratch on 3,000 NVIDIA H200 GPUs and is Mistral AIโ€™s first MoE model since the Mixtral series. Both base and instruction-fine-tuned versions are released under the Apache 2.0 license. The model supports image understanding (multimodal input) and multilingual conversations.

Mistral Large 3 is available through Mistral AI Studio, Amazon Bedrock, Azure AI Foundry, Hugging Face, IBM WatsonX, OpenRouter, Fireworks, and Together AI. The model weights can run on a single 8ร—A100 or 8ร—H100 node with vLLM, and in NVFP4 format on Blackwell NVL72 systems.

Classification
LLMMultimodal
Family: Mistral
Access & deployment
APIDownloadHosted
CloudLocal
Weights: Open source
Key parameters
๐Ÿ“ Context: 256k
๐Ÿงฉ Parameters: 675B total / 41B active
๐Ÿ“ฅ Input: text, image

Technical specification

Context window
256k
tokens
Parameters
675B total / 41B active
parameters
License
Apache 2.0
Modalities
โฌ‡ Input
textimage
โฌ† Output
textcode

Capabilities and applications

Native model capabilities
Image understanding
Analysing and interpreting the content of images.
Category: vision
Multilingual
Competence in many natural languages (from a few to over a hundred): understanding, generation, translation, and code-switching within a single conversation. Frontier models support a wide range of languages with comparable quality.
Category: language
Multimodal understanding
Category: multimodal
Function Calling
Category: planning
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Long context
Support for large context windows โ€” tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
OCR
Recognising text within images and documents.
Category: vision

Benchmark results

1 benchmark
LMArena (leaderboard)
Ranking wsrod modeli open-source (OSS) ยท Mistral Large 3 ranked #6 among open-source (OSS) models on the LMArena leaderboard per Mistral AI's announcement.
#6pozycja
๐Ÿ“… 2 Dec 2025
Source: https://mistral.ai/news/mistral-3

Pricing

Technical architecture

Core Architecture
Training Techniques

Deployment and security

๐Ÿ”’ Security / Enterprise
โœ“ Verified enterprise information

Open-weight model under Apache 2.0 - self-hosting / on-premises deployment possible (full data control). Also available on Amazon Bedrock, Microsoft Azure AI Foundry and Hugging Face with the providers' enterprise controls; supports secure integration with internal tools (function calling).

Updated: 31 Jul 2026โ†— Security documentation