Pixtral 12B
<|reference_start|>Pixtral 12B: We introduce Pixtral-12B, a 12--billion-parameter multimodal language model. Pixtral-12B is trained to understand both natural images and documents, achieving leading performance on various multimodal benchmarks, surpassing a number of larger models. Unlike many open-source models, Pixtral is also a cutting-edge text model for its size, and does not compromise on natural language performance to excel in multimodal tasks. Pixtral uses a new vision encoder trained from scratch, which allows it to ingest images at their natural resolution and aspect ratio. This gives users flexibility on the number of tokens used to process an image. Pixtral is also able to process any number of images in its long context window of 128K tokens. Pixtral 12B substanially outperforms other open models of similar sizes (Llama-3.2 11B \& Qwen-2-VL 7B). It also outperforms much larger open models like Llama-3.2 90B while being 7x smaller. We further contribute an open-source benchmark, MM-MT-Bench, for evaluating vision-language models in practical scenarios, and provide detailed analysis and code for standardized evaluation protocols for multimodal LLMs. Pixtral-12B is released under Apache 2.0 license.<|reference_end|>
@article{agrawal2024pixtral,
    title={Pixtral 12B},
    author={Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, Baptiste Bout,
  Devendra Chaplot, Jessica Chudnovsky, Diogo Costa, Baudouin De Monicault,
  Saurabh Garg, Theophile Gervet, Soham Ghosh, Am'elie H'eliou, Paul Jacob,
  Albert Q. Jiang, Kartik Khandelwal, Timoth'ee Lacroix, Guillaume Lample,
  Diego Las Casas, Thibaut Lavril, Teven Le Scao, Andy Lo, William Marshall,
  Louis Martin, Arthur Mensch, Pavankumar Muddireddy, Valera Nemychnikova,
  Marie Pellat, Patrick Von Platen, Nikhil Raghuraman, Baptiste Rozi`ere,
  Alexandre Sablayrolles, Lucile Saulnier, Romain Sauvestre, Wendy Shang, Roman
  Soletskyi, Lawrence Stewart, Pierre Stock, Joachim Studnia, Sandeep
  Subramanian, Sagar Vaze, Thomas Wang, Sophia Yang},
    journal={arXiv preprint arXiv:2410.07073},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.07073},
    primaryClass={cs.CV cs.CL}
}