[Submitted on 25 May 2026 (
[v1](https://arxiv.org/abs/2605.26064v1)), last revised 27 May 2026 (this version, v2)]# Title:Paris 2.0: A Decentralized Diffusion Model for Video Generation
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Abstract:We present Paris 2.0, the first video generation model pre-trained through decentralized computation. Its training recipe builds upon Paris 1.0 ([arXiv:2510.03434]), the first ever open-weight Decentralized Diffusion Model (DDM), which showed that image generation can be trained without a monolithic GPU cluster. However, temporally coherent video generation had remained an open problem under decentralized training, and Paris 2.0 closes it.
In low-resolution text-to-video training, against a monolithic model trained on the same data under a matched total compute budget, Paris 2.0 cuts Frechet Video Distance (FVD) from 561.04 to 279.01, a ~2.0x improvement, and lifts CLIP text-video similarity and aesthetic score.
Submission history #
From: Marcos Villagra [[view email](/show-email/b05cc136/2605.26064)]
**Mon, 25 May 2026 17:27:22 UTC (2,417 KB)**
[[v1]](/abs/2605.26064v1)**[v2]** Wed, 27 May 2026 11:28:25 UTC (3,047 KB)
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