Ministral 3 (Ministral 3)

Alexander H. Liu,Kartik Khandelwal,Sandeep Subramanian,Victor Jouault,Abhinav Rastogi,Adrien Sadé,Alan Jeffares,Albert Jiang,Alexandre Cahill,Alexandre Gavaudan,Alexandre Sablayrolles,Amélie Héliou,Amos You,Andy Ehrenberg,Andy Lo,Anton Eliseev,Antonia Calvi,Avinash Sooriyarachchi,Baptiste Bout,Baptiste Rozière,Baudouin De Monicault,Clémence Lanfranchi,Corentin Barreau,Cyprien Courtot,Daniele Grattarola,Darius Dabert,Diego de las Casas,Elliot Chane-Sane,Faruk Ahmed,Gabrielle Berrada,Gaëtan Ecrepont,Gauthier Guinet,Georgii Novikov,Guillaume Kunsch,Guillaume Lample,Guillaume Martin,Gunshi Gupta,Jan Ludziejewski,Jason Rute,Joachim Studnia,Jonas Amar,Joséphine Delas,Josselin Somerville Roberts,Karmesh Yadav,Khyathi Chandu,Kush Jain,Laurence Aitchison,Laurent Fainsin,Léonard Blier,Lingxiao Zhao,Louis Martin,Lucile Saulnier,Luyu Gao,Maarten Buyl,Margaret Jennings,Marie Pellat,Mark Prins,Mathieu Poirée,Mathilde Guillaumin,Matthieu Dinot,Matthieu Futeral,Maxime Darrin,Maximilian Augustin,Mia Chiquier,Michel Schimpf,Nathan Grinsztajn,Neha Gupta,Nikhil Raghuraman,Olivier Bousquet,Olivier Duchenne,Patricia Wang,Patrick von Platen,Paul Jacob,Paul Wambergue,Paula Kurylowicz,Pavankumar Reddy Muddireddy,Philomène Chagniot,Pierre Stock,Pravesh Agrawal,Quentin Torroba,Romain Sauvestre,Roman Soletskyi,Rupert Menneer,Sagar Vaze,Samuel Barry,Sanchit Gandhi,Siddhant Waghjale,Siddharth Gandhi,Soham Ghosh,Srijan Mishra,Sumukh Aithal,Szymon Antoniak,Teven Le Scao,Théo Cachet,Theo Simon Sorg,Thibaut Lavril,Thiziri Nait Saada,Thomas Chabal,Thomas Foubert,Thomas Robert,Thomas Wang,Tim Lawson,Tom Bewley,Tom Bewley,Tom Edwards,Umar Jamil,Umberto Tomasini,Valeriia Nemychnikova,Van Phung,Vincent Maladière,Virgile Richard,Wassim Bouaziz,Wen-Ding Li,William Marshall,Xinghui Li,Xinyu Yang,Yassine El Ouahidi,Yihan Wang,Yunhao Tang,Zaccharie Ramzi

from arxiv, Release page: https://mistral.ai/news/mistral-3 ; Models available at https://huggingface.co/collections/mistralai/ministral-3

We introduce the Ministral 3 series, a family of parameter-efficient dense language models designed for compute and memory constrained applications, available in three model sizes: 3B, 8B, and 14B parameters. For each model size, we release three variants: a pretrained base model for general-purpose use, an instruction finetuned, and a reasoning model for complex problem-solving. In addition, we present our recipe to derive the Ministral 3 models through Cascade Distillation, an iterative pruning and continued training with distillation technique. Each model comes with image understanding capabilities, all under the Apache 2.0 license.

翻译：我们推出 Ministral 3 系列，这是一个专为计算和内存受限应用设计的参数高效稠密语言模型家族，提供三种模型规模：30亿、80亿和140亿参数。针对每种模型规模，我们发布了三个变体：一个用于通用目的的预训练基础模型、一个经过指令微调的模型，以及一个用于复杂问题求解的推理模型。此外，我们介绍了通过级联蒸馏（Cascade Distillation）——一种结合迭代剪枝与持续蒸馏训练的迭代技术——来推导 Ministral 3 模型的完整方法。所有模型均具备图像理解能力，并在 Apache 2.0 许可证下发布。