Mistral Large 2

Mistral Large 2 refines the Mistral family with higher accuracy and broader coverage across reasoning, software engineering, and cross-lingual tasks. It’s a dense, text-in/text-out model that follows instructions reliably and produces step-by-step, grounded answers. Developers can take advantage of built-in function calling, structured JSON output modes, and streaming, which allow seamless integration into agent frameworks, retrieval-augmented generation setups, and automation pipelines.

The model is optimized for both throughput and quality: its long context window (~128K) enables multi-document reasoning, codebase-level tasks, and extended chats, while quantization and efficient inference kernels keep latency and cost manageable. It’s open weights under a permissive license, so teams can deploy it locally, fine-tune with LoRA or adapters, or serve at scale via cloud runtimes like vLLM.

In practice, Mistral Large 2 is used for enterprise copilots, multilingual knowledge assistants, repo-level coding agents, and analytical workflows that require accuracy and reproducibility. It’s the “all-purpose” high-end model from Mistral—compact enough for practical serving, but powerful enough to compete with other frontier-scale open LLMs.