PAN 2 开源：动作条件世界模型，可生成最长 20 秒结果预测视频
做 Agent 或机器人训练的朋友可以关注：PAN 2 开源了，输入一个动作描述，语言模型先推演剧情，29B 视频模型再渲染出最长 20 秒的物理结果，等于把试错搬进了仿真，不用在真实环境里烧成本。
PAN 2 是一个免费开源的动作条件世界模型（action-conditioned world model），用户描述一个动作后，它能生成最长 20 秒的视频，展示该动作在物理世界中会引发的结果。其核心价值在于把智能体的试错成本从真实环境转移到仿真环境中。
技术上它采用两阶段分工：先由一个语言模型推理出事件走向的"剧情"，再由一个 29B 参数的视频模型负责渲染画面。这种拆分让模型既能理解动作语义，又能保证生成画面的物理一致性。
对做 Agent 训练的开发者来说，这类世界模型意味着可以在模拟里低成本跑大量失败案例，而不必在真实环境中承担试错开销。
Agents learn from trial and error. The expensive part is the error. A world model moves the error into simulation, which is the whole case for something like PAN 2.
This is a free, open "action-conditioned world model".
Takes an action you describe, and generates up to 20 seconds of video showing what would physically happen next. Its new trick is splitting the job in 2: a language model first works out the plot, then a 29B video model renders it.
This report is categorized under AITOP's "Models" desk. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include PAN 2, 世界模型, 开源模型, 视频生成.
Source attribution: curated from rohanpaul_ai (@rohanpaul_ai).
