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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
VILA is a family of state-of-the-art vision language models (VLMs) for diverse multimodal AI tasks across the edge, data center, and cloud.
| Date | Stars |
|---|---|
| 2026-07-31 | 3846 |
| 2026-08-03 | 3846 |
| 2026-08-06 | 3850 |
Today
+4 stars today
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growth rate 0.00%/day
# VILA: Optimized Vision Language Models [](CODE_LICENSE) [](MODEL_LICENSE) [](https://www.python.org/downloads/release/python-3100/) [arXiv](https://arxiv.org/abs/2412.04468) / [Demo](https://vila.hanlab.ai/) / [Models](https://huggingface.co/collections/Efficient-Large-Model/nvila-674f8163543890b35a91b428) / [Subscribe](https://forms.gle/6nf1QdPYdvC2vgxM8) ## 💡 Introduction VILA is a family of open VLMs designed to optimize both efficiency and accuracy for efficient video understanding and multi-image understanding. ## 💡 News - \[2025/7\] We release [OmniVinci](https://github.com/NVlabs/OmniVinci), a state-of-the-art visual-audio joint understanding omni-modal LLM built upon VILA codebase! - \[2025/7\] We release [Long-RL](https://github.com/NVlabs/Long-RL) that supports RL training on VILA/LongVILA/NVILA models with long videos. - \[2025/6\] We release [PS3 and VILA-HD](https://nvlabs.github.io/PS3/). PS3 is a vision encoder that scales up vision pre-training to 4K resolution. VILA-HD is VILA with PS3 as the vision encoder and shows superior performance and efficiency in understanding high-resolution detail-rich images. - \[2025/1\] As of January 6, 2025 VILA is now part of the new Cosmos Nemotron vision language models. - \[2024/12\] We release [NVILA](https://arxiv.org/abs/2412.04468) (a.k.a VILA2.0) that explores the full stack efficiency of multi-modal design, achieving cheaper training, faster deployment and better performance. - \[2024/12\] We release [LongVILA](./longvila/README.md) that supports long video understanding, with long-context VLM with more than 1M context length and multi-modal sequence parallel system. - \[2024/10\] VILA-M3, a SOTA medical VLM finetuned on VILA1.5 is released! VILA-M3 significantly outperforms Llava-Med and on par w/ Med-Gemini and is fully opensourced! [code](https://github.com/Project-MONAI/VLM#-news) [model](https://huggingface.co/MONAI) - \[2024/10\] We release [VILA-U](https://github.com/mit-han-lab/vila-u): a Unified foundation model that integrates Video, Image, Language understanding and generation. - \[2024/07\] VILA1.5 also ranks 1st place (OSS model) on [MLVU test leaderboard](https://github.com/JUNJIE99/MLVU). - \[2024/06\] VILA1.5 is now the best open sourced VLM on [MMMU leaderboard](https://mmmu-benchmark.github.io/#leaderboard) and [Video-MME](https://video-mme.github.io/home_page.html#leaderboard) leaderboard! - \[2024/05\] We release VILA-1.5, which offers **video understanding capability**. VILA-1.5 comes with four model sizes: 3B/8B/13B/40B. <details> <summary>Click to show more news</summary> - \[2024/05\] We release [AWQ](https://arxiv.org/pdf/2306.00978.pdf)-quantized 4bit VILA-1.5 models. VILA-1.5 is efficiently deployable on diverse NVIDIA GPUs (A100, 4090, 4070 Laptop, Orin, Orin Nano) by [TinyChat](https://github.com/mit-han-lab/llm-awq/tree/main/tinychat) and [TensorRT-LLM](demo_trt_llm) backends. - \[2024/03\] VILA has been accepted by CVPR 2024! - \[2024/02\] We release [AWQ](https://arxiv.org/pdf/2306.00978.pdf)-quantized 4bit VILA models, deployable on Jetson Orin and laptops through [TinyChat](https://github.com/mit-han-lab/llm-awq/tree/main/tinychat) and [TinyChatEngine](https://github.com/mit-han-lab/TinyChatEngine). - \[2024/02\] VILA is released. We propose interleaved image-text pretraining that enables **multi-image** VLM. VILA comes with impressive in-context learning capabilities. We open source everything: including training code, evaluation code, datasets, model ckpts. - \[2023/12\] [Paper](https://arxiv.org/abs/2312.07533) is on Arxiv! </details> ## Performance ## Image Benchmarks  ### Video Benchmarks 
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Ligeng Zhu · United States
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Baifeng Shi · Physical Intelligence · United States
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yukang · NVIDIA · United States
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Zhijian Liu · Assistant Professor at @ucsd (@z-lab), and Research Scientist at @nvidia
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4
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Yixin Dong · Carnegie Mellon University · United States
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Wei-Ming Chen
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Johnny · NVIDIA · Spain
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Emmanuel Ferdman · Israel
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Eduardo Salinas · Microsoft · United States
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Xiuyu Li · United States
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Dacheng Li
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Song · MIT, NVIDIA
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:db68dc96fb309fac, desc:multimodal, desc:vision-language