Model Detail
Mistral Large 2411
—Mistral Large 2411 is a large language model released by Mistral AI. And supports text+file->text inputs.
Open-LLM-Leaderboard scoring places it at MMLU-Pro 51, GPQA 25, IFEval 84, BBH 53, giving a sense of how it handles instruction following, reasoning, and graduate-level QA in absolute terms.
Mistral Large 2411 is priced at $2/M input tokens and $6/M output tokens. Operationally the model offers a 128K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. Pricing in this range is the working middle of the API market — neither the cheapest nor the most expensive option per token, so cost-fit is usually a function of how much output you generate.
Mistral Large 2411 ships as a MistralForCausalLM / 💬 chat models (RLHF, DPO, IFT, ...) architecture. The published knowledge cutoff is 2024-07-31, so newer events will not be reflected in zero-shot answers without retrieval.
Mistral Large 2411 is best fit for general-purpose chat and instruction-following workloads. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Mistral’s new 1T model aims to leapfrog closed and open rivals
French AI lab Mistral AI has released Mistral Large 4, a new large multimodal model aiming to leapfrog both American and Chinese rivals.
Mistral raises €3B as sovereign AI becomes big business
The French AI lab has raised €3 billion at a €21 billion valuation in a Series D round led by Samsung, Scaleup Europe, and PSG Equity.
Mistral is rumored to be raising €3B at €20B valuation
The funding round would value the company at around €20 billion (about $23.15 billion), nearly double its Series C valuation of €11.7 billion.
Making Knowledge Accessible: Divergent Readability-Accuracy Strategies of Mistral and QWen in Biomedical Text Simplification
arXiv:2511.05080v4 Announce Type: replace Abstract: The growing public demand for accessible biomedical information calls for scalable text simplification. While large language models (LLMs) offer solutions, they too struggle with balancing improved readability against preservation of meaning. This
Benchmarking Linguistic Adaptation in Comparable-Sized LLMs: A Study of Llama-3.1-8B, Mistral-7B-v0.1, and Qwen3-8B on Romanized Nepali
arXiv:2604.14171v1 Announce Type: new Abstract: Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains critically underresourced in the landscape of Large Language Models (LLMs). This study presents a sy
Mistral AI raises $830M in debt to set up a data center near Paris
Mistral aims to start operating the data center by the second quarter of 2026.
