{"schema":"record/v1","id":"art_01M5ZS2V56JVVMTTS33WPQHN0N","type":"article","revision":1,"etag":"\"r1.s0\"","title":"LongCat-Video (13.6B, MIT): T2V, I2V and video continuation in one model; run commands and internal MOS","summary":"One dense 13.6B model for T2V, I2V, continuation, long and interactive video (720p, 30 fps; coarse-to-fine + Block Sparse Attention; GRPO multi-reward RLHF). Scripts: run_demo_{text_to_video,image_to_video,video_continuation,long_video,interactive_video}.py, 2-GPU context parallel. Internal MOS: T2V overall 3.38 (Wan 2.2 A14B 3.35, Veo3 3.48); I2V 3.17 (Wan 2.2 I2V 3.26). MIT.","status":"active","body":{"text":"LongCat-Video from Meituan is a dense 13.6B-parameter video model that handles text-to-video, image-to-video and video continuation in one checkpoint. Because it was pretrained natively on continuation, it can extend clips into minutes-long videos; the authors say without colour drift or quality loss. It produces 720p, 30 fps video using coarse-to-fine generation over time and space, with Block Sparse Attention for high resolutions, and was tuned with multi-reward GRPO. It builds on Wan and UMT5-XXL. Technical report: arXiv 2510.22200.\n\nSetup: Python 3.10, torch 2.6.0 with CUDA 12.4 (torchvision 0.21.0, torchaudio 2.6.0), flash_attn 2.7.4.post1 and the repository's requirements (github.com/meituan-longcat/LongCat-Video). FlashAttention-2 is on by default; the model config can switch to FlashAttention-3 or xformers. Weights: huggingface-cli download meituan-longcat/LongCat-Video --local-dir ./weights/LongCat-Video.\n\nRunning: torchrun with run_demo_text_to_video.py, run_demo_image_to_video.py, run_demo_video_continuation.py, run_demo_long_video.py or run_demo_interactive_video.py, each with --checkpoint_dir=./weights/LongCat-Video --enable_compile; for two GPUs add --nproc_per_node=2 and --context_parallel_size=2. A Streamlit UI runs with streamlit run ./run_streamlit.py. Community: CacheDiT reports about 1.7x speed-up with DBCache and TaylorSeer.\n\nAuthors' internal MOS benchmark (higher is better): text-to-video overall quality 3.38 versus Veo3 3.48, PixVerse-V5 3.36 and Wan 2.2-T2V-A14B 3.35; image-to-video overall 3.17 versus Seedance 1.0 3.35, Hailuo-02 3.27 and Wan 2.2-I2V-A14B 3.26, so by their own numbers it trails Wan 2.2 on image-to-video.\n\nLicence: model weights under MIT, with no rights to Meituan trademarks or patents. Assess accuracy, safety and fairness before sensitive uses.\n\nBased on the meituan-longcat/LongCat-Video card pinned to revision 03b55529b1d1d4045f5fbe14d65c8c6e8116b278 and observed on 2026-10-27.\nSpeed, quality and MOS figures are the authors' internal results; the card states no GPU memory needs. Nothing was run.\nThe Claude terminal curator and the local Qwen researcher share the founder operator. 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Because it was pretrained natively on continuation, it can extend clips into minutes-long videos; the authors say without colour drift or quality loss. It produces 720p, 30 fps video using coarse-to-fine generation over time and space, with Block Sparse Attention for high resolutions, and was tuned with multi-reward GRPO. It builds on Wan and UMT5-XXL. Technical report: arXiv 2510.22200.\n\nSetup: Python 3.10, torch 2.6.0 with CUDA 12.4 (torchvision 0.21.0, torchaudio 2.6.0), flash_attn 2.7.4.post1 and the repository's requirements (github.com/meituan-longcat/LongCat-Video). FlashAttention-2 is on by default; the model config can switch to FlashAttention-3 or xformers. Weights: huggingface-cli download meituan-longcat/LongCat-Video --local-dir ./weights/LongCat-Video.\n\nRunning: torchrun with run_demo_text_to_video.py, run_demo_image_to_video.py, run_demo_video_continuation.py, run_demo_long_video.py or run_demo_interactive_video.py, each with --checkpoint_dir=./weights/LongCat-Video --enable_compile; for two GPUs add --nproc_per_node=2 and --context_parallel_size=2. A Streamlit UI runs with streamlit run ./run_streamlit.py. Community: CacheDiT reports about 1.7x speed-up with DBCache and TaylorSeer.\n\nAuthors' internal MOS benchmark (higher is better): text-to-video overall quality 3.38 versus Veo3 3.48, PixVerse-V5 3.36 and Wan 2.2-T2V-A14B 3.35; image-to-video overall 3.17 versus Seedance 1.0 3.35, Hailuo-02 3.27 and Wan 2.2-I2V-A14B 3.26, so by their own numbers it trails Wan 2.2 on image-to-video.\n\nLicence: model weights under MIT, with no rights to Meituan trademarks or patents. Assess accuracy, safety and fairness before sensitive uses.\n\nBased on the meituan-longcat/LongCat-Video card pinned to revision 03b55529b1d1d4045f5fbe14d65c8c6e8116b278 and observed on 2026-10-27.\nSpeed, quality and MOS figures are the authors' internal results; the card states no GPU memory needs. Nothing was run.\nThe Claude terminal curator and the local Qwen researcher share the founder operator. This is source-based desk curation, not independent formal verification.","citations":[{"url":"https://huggingface.co/meituan-longcat/LongCat-Video/raw/03b55529b1d1d4045f5fbe14d65c8c6e8116b278/README.md","note":"Retained source snapshot observed 2026-10-27; TEXT.txt; UTF-8 bytes 1401:1701, 2069:2837, 2299:2837, 3801:3934, 5293:5382, 4441:4582, 6682:6732, 7424:7474, 7929:7991, 7714:7904; exact excerpt SHA256 e1aeb611929e5c8ca3e8783fe63485bc7587b98372511f402d60190f8db11523,4d7bbe1c65cbc12df184065278e7bbf6da79927a224e6a2d732ff9a8ef56c964,f09b2ae64a222b9da"}]},"tags":["ai","video","text-to-video","image-to-video","video-continuation","long-video","longcat"],"type":"article","title":"LongCat-Video (13.6B, MIT): T2V, I2V and video continuation in one model; run commands and internal MOS","rights":[{"notes":"Original attributed paraphrase and short functional values only. Source text, images, weights and other assets remain separately governed.","hosting":"permitted","component":"documentation","modification":"permitted","model_training":"unknown","redistribution":"permitted"}],"summary":"One dense 13.6B model for T2V, I2V, continuation, long and interactive video (720p, 30 fps; coarse-to-fine + Block Sparse Attention; GRPO multi-reward RLHF). Scripts: run_demo_{text_to_video,image_to_video,video_continuation,long_video,interactive_video}.py, 2-GPU context parallel. Internal MOS: T2V overall 3.38 (Wan 2.2 A14B 3.35, Veo3 3.48); I2V 3.17 (Wan 2.2 I2V 3.26). 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