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Peking University, Tsinghua, Alibaba open-source SparkDiffusion for 265x faster AI video generation · 2…

By PulseAugur Editorial · [2 sources] ·

Researchers from Peking University, Tsinghua University, and Alibaba Group have jointly released SparkDiffusion, an open-source AI framework designed to accelerate video generation. This new framework reportedly achieves up to a 265x speedup, reducing the time to generate a 720P Wan2.1 14B video from nearly an hour (4,769 seconds) to just 18 seconds on a single RTX 5090 GPU. The code and model weights for SparkDiffusion are now publicly available. AI

IMPACT Accelerates AI video generation, potentially enabling faster iteration and broader application of generative video models.

RANK_REASON Open-source release of an AI model/framework by academic and corporate entities.

Read on Pandaily →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Peking University, Tsinghua, Alibaba open-source SparkDiffusion for 265x faster AI video generation · 2…

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41 / 100
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Research
Open-source release of an AI model/framework by academic and corporate entities.
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2 independent sources
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model release, infra
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [2]

  1. Pandaily TIER_1 English(EN) · [email protected] (Pandaily) ·

    Peking University, Tsinghua and Alibaba Open-Source SparkDiffusion for Up to 265x Faster Wan Video Generation

    SparkDiffusion pairs 97% sparse attention, 3-step distillation and FP8 to cut a 720P Wan2.1 14B video from 4,769 to 18 seconds on one RTX 5090, a 265x speedup. Code and weights are open.

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Peking University, Tsinghua and Alibaba have open-sourced SparkDiffusion, an AI video generation accelerator. The framework cuts Wan 2.1 video generation time b

    Peking University, Tsinghua and Alibaba have open-sourced SparkDiffusion, an AI video generation accelerator. The framework cuts Wan 2.1 video generation time by 265x, from 4,769 seconds to 18 seconds on an RTX 5090. Code and weights are available on GitHub and Hugging Face. http…

    LINKS pandaily.com/sparkdiffusion-open-source-w…

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