Open-weights sparse mixture-of-experts model from Mistral AI: 46.7B total parameters (12.9B active per token), 32K context window, Apache 2.0 license.
Context window
32K
tokens
Parameters
46.7B total / 12.9B active
parameters
Release date
11 December 2023
Access:APIDownloadDeployment:๐ป Localโ Cloud
Overview
Access & deployment
APIDownload
LocalCloud
Weights: Open source
Key parameters
๐ Context: 32K
๐งฉ Parameters: 46.7B total / 12.9B active
โ Fine-tuning
๐ฅ Input: text
Technical specification
Context window
32K
tokens
Parameters
46.7B total / 12.9B active
parameters
License
Apache 2.0
Features:โ Fine-tuning
Modalities
โฌ Input
text
โฌ Output
textcode
Capabilities and applications
Native model capabilities
Language modeling
Ability to predict subsequent tokens and generate coherent natural-language text based on the preceding context.
Category: language
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
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
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
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Benchmark results
2 benchmarks
MT-Bench
8.30
๐ mistral.ai/news/mixtral-of-experts
Score for Mixtral 8x7B Instruct (SFT + DPO).
MMLU
accuracy
70.6%%
๐ mistral.ai/news/mixtral-of-experts
Technical architecture
Core Architecture
Model Form
