开源5B多人世界模型MIRA：用DINOv3表征缓解长时漂移，可实时模拟《火箭联盟》2v2对抗

开源5B多人世界模型MIRA：用DINOv3表征缓解长时漂移，可实时模拟《火箭联盟》2v2对抗

2026-07-07 19:30

ChainThink 消息，7 月 7 日，据相关发布，AI 研究机构 General Intuition 联合法国 AI 实验室 Kyutai 及 Epic Games 推出开源 50 亿参数多人交互世界模型 MIRA，可仅基于历史画面和玩家按键，实时模拟《火箭联盟》2v2 对抗，无需物理引擎、渲染引擎或显式 3D 表示参与推理。

MIRA 采用基于视频潜在空间的生成式模拟路线，并将潜在预测空间建立在冻结的通用视觉编码器 DINOv3-L 之上，以缓解长时预测中的画面漂移与发散。

其多视角方案将四名玩家视角拼接为统一网格，以提升跨视角空间一致性。训练中引入的动作丢弃机制，可在缺少部分动作流时补全未被指令控制车辆的行为。

当前 MIRA 可在单张英伟达 B200 显卡上以 20 帧/秒实时运行。

团队同时开源训练与推理代码，并发布 Rocket Science 数据集，包含 1000 小时比赛、四视角合计约 4000 小时的视频、动作流和物理状态数据；

完整训练使用了约 1 万小时的干净对局数据。

Disclaimer: Contains third-party opinions, does not constitute financial advice

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