Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation
World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos. Moreover, scaling these models could unlock emergent capabilities in visual perception, understanding, and reasoning, paving the way for a new paradigm that moves beyond current LLM-centric vision foundation models. A key breakthrough empowering them is the semi-autoregressive (block-diffusion) decoding paradigm, which merges the strengths of diffusion and autoregressive methods by generating video tokens in block-applying diffusion within each block while conditioning on previous ones, resulting in more coherent and stable video sequences. Crucially, it overcomes limitations of standard video diffusion by reintroducing LLM-style KV Cache management, enabling efficient, variable-length, and high-quality generation.
  Therefore, Inferix is specifically designed as a next-generation inference engine to enable immersive world synthesis through optimized semi-autoregressive decoding processes. This dedicated focus on world simulation distinctly sets it apart from systems engineered for high-concurrency scenarios (like vLLM or SGLang) and from classic video diffusion models (such as xDiTs). Inferix further enhances its offering with interactive video streaming and profiling, enabling real-time interaction and realistic simulation to accurately model world dynamics. Additionally, it supports efficient benchmarking through seamless integration of LV-Bench, a new fine-grained evaluation benchmark tailored for minute-long video generation scenarios. We hope the community will work together to advance Inferix and foster world model exploration.
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Inferix Team
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Tianyu Feng
6927bc37243b2216fb75cd3e
Yizeng Han
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Jiahao He
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Yuanyu He
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Xi Lin
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Teng Liu
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Hanfeng Lu
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Jiasheng Tang
claimed_verified
2025-11-28T13:48:58.845Z
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Tang
Jiasheng1110
user
Jiasheng1110
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Wei Wang
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Zhiyuan Wang
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Jichao Wu
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Mingyang Yang
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Yinghao Yu
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Zeyu Zhang
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2025-11-27T09:59:06.036Z
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Zeyu Zhang
SteveZeyuZhang
user
SteveZeyuZhang
6927bc37243b2216fb75cd4b
Bohan Zhuang
Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation
World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic, and interactive high-quality videos. Moreover, scaling these models could unlock emergent capabilities in visual perception, understanding, and reasoning, paving the way for a new paradigm that moves beyond current LLM-centric vision foundation models. A key breakthrough empowering them is the semi-autoregressive (block-diffusion) decoding paradigm, which merges the strengths of diffusion and autoregressive methods by generating video tokens in block-applying diffusion within each block while conditioning on previous ones, resulting in more coherent and stable video sequences. Crucially, it overcomes limitations of standard video diffusion by reintroducing LLM-style KV Cache management, enabling efficient, variable-length, and high-quality generation.
  Therefore, Inferix is specifically designed as a next-generation inference engine to enable immersive world synthesis through optimized semi-autoregressive decoding processes. This dedicated focus on world simulation distinctly sets it apart from systems engineered for high-concurrency scenarios (like vLLM or SGLang) and from classic video diffusion models (such as xDiTs). Inferix further enhances its offering with interactive video streaming and profiling, enabling real-time interaction and realistic simulation to accurately model world dynamics. Additionally, it supports efficient benchmarking through seamless integration of LV-Bench, a new fine-grained evaluation benchmark tailored for minute-long video generation scenarios. We hope the community will work together to advance Inferix and foster world model exploration.
Inferix is a next-generation inference engine designed for immersive world synthesis using semi-autoregressive decoding, combining diffusion and autoregressive methods for high-quality, real-time video generation and interaction.
world models agentic AI embodied AI gaming visual perception understanding reasoning semi-autoregressive block-diffusion diffusion autoregressive methods video tokens KV Cache management Inferix vLLM SGLang xDiTs interactive video streaming profiling LV-Bench minute-long video generation