Model card
Mistral Large 2 is Mistral AI's premier proprietary model, engineered specifically for high-reasoning tasks and complex multilingual workflows. With 123B parameters, it occupies a strategic middle ground: it delivers performance comparable to top-tier closed models while maintaining significantly higher efficiency for enterprise-scale deployment. For developers, the standout feature is its 128k context window, which allows for deep document analysis and extensive codebase reasoning without immediate memory degradation. Unlike many general-purpose models that struggle with nuanced linguistic shifts, Mistral Large 2 excels in multilingual code generation and logical reasoning across diverse languages. It is designed for seamless integration into RAG pipelines and agentic workflows where precision and instruction-following are non-negotiable. If your use case requires a robust engine for sophisticated reasoning or high-throughput multilingual processing, this model provides a highly optimized alternative to the most bloated frontier models.
Model files and versions
Download this model
We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.
mistralai/Mistral-Large-2Install the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model mistralai/Mistral-Large-2README.md is used as an example; replace it with another repository file when needed.
modelscope download --model mistralai/Mistral-Large-2 README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('mistralai/Mistral-Large-2')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/mistralai/Mistral-Large-2.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/mistralai/Mistral-Large-2.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
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