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Paper · arXiv 2607.18703

Generative World Renderer at the Speed of Play

Guixu Lin, Zheng-Hui Huang, Siqi Yang, Ming-Hsuan Yang, Kaipeng Zhang, Zhixiang Wang

84 upvotesJuly 21, 2026arXiv 预印本
AI 摘要

AlayaRenderer-Flash accelerates a generative world renderer to real-time speeds via few-step autoregressive streaming and distilled codecs while preserving structured scene dynamics.

generative world rendererG-bufferautoregressive streaming modeldistilled codecslatent encodingframe reconstructioninference costtemporal consistency

Abstract

Generative world renderer AlayaRenderer receives structured world states exported from physics engines and synthesizes RGB frames. Unlike models that generate frames from text/control-hints prompts, AlayaRenderer preserves scene structure without altering the underlying world dynamics. This demonstrates an alternative path toward interactive world modeling and user-controllable play. However, the original AlayaRenderer is too computationally expensive for real-time deployment. This technical report introduces AlayaRenderer-Flash, a real-time-oriented generative forward world renderer that pushes AlayaRenderer from 0.56 FPS to 31.54 FPS, reaching the speed of play. AlayaRenderer-Flash reformulates the original renderer as a few-step autoregressive streaming model and introduces lightweight distilled codecs for efficient latent encoding and frame reconstruction. It retains the teacher model's G-buffer and text-prompt interfaces while enabling continuous rendering over input streams of unbounded length. We evaluate AlayaRenderer-Flash on G-buffer streams across content preservation, temporal consistency, cross-window stability, prompt controllability, and runtime efficiency. Our results show that AlayaRenderer-Flash substantially reduces inference cost while preserving the core rendering capabilities of the teacher model. By integrating AlayaRenderer-Flash with a physics engine, we build a fully playable generative world running at 30 FPS.

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