MBZUAI Releases PAN 2 Open World Model for Simulative Reasoning
MBZUAI's Institute of Foundation Models released PAN 2, an open foundation world model for physical intelligence built around simulative reasoning that lets agents play out outcomes before acting. It splits reasoning into two tracks: an LLM determines what happens, when, and how the camera moves and writes it as text, while a 29B diffusion model trained from scratch renders that text into visuals. Ablating the LLM collapses multi-step performance to 8.7% correct steps with no completed plans, whereas the combined system reaches 75.1% correct steps and 34.0% fully completed plans.
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Rohan Paul (@rohanpaul_ai) · 2026-11-10 18
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:
