MBZUAI 基础模型研究所（IFM）发布面向物理智能的开放基础世界模型 PAN 2，目标是让智能体在行动前先模拟推演结果。它把推理拆成两部分：LLM 负责判断发生什么、何时发生以及镜头如何移动并写成文本，一个从零训练的 29B 扩散模型再把文本转成画面。
MBZUAI's Institute of Foundation Models (IFM) just released PAN 2, an open foundation world model for physical intelligence.
It's built towards simulative reasoning: letting an agent play out what happens before it acts.
It works with two kinds of reasoning, each with its own job:
Conceptual: an LLM works out what happens, when, and how the camera moves, then writes it down as text.
Perceptual: a 29B diffusion model, trained from scratch, turns that text into what you see.
Take the LLM out, and multi-step tasks fall apart: 8.7% of steps right, no plan finished. Getting the order of actions right is the LLM's job.
With both, PAN 2 gets 75.1% of steps right and finishes 34.0% of plans in full, the highest among the models IFM tested. Every step has to hold for a plan to work.
More details in the technical blog:
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来源：Rohan Paul · x.com