MagicAtom's EchoPolicy-0 and MagicBrain Frameworks Achieve Top Performance in MolmoSpaces Benchmark
魔法原子具身 Agent 框架拿下 MolmoSpaces 全球第一 让 VLA 从“演示可用”逼近“产线可用”
MagicAtom's EchoPolicy-0 framework achieved a 75.4% average success rate in MolmoSpaces Combined benchmark, ranking first globally, while MagicBrain achieved 72.4% with a 94.4% grasp success rate. Both frameworks address challenges in VLA by integrating visual language models with geometric tools and action policies, improving task execution and generalization in complex environments.
The report details specific robot-learning mechanisms (EchoPolicy-0's VLM-guided trajectory selection and MagicBrain's In-Context Visual Guidance) and presents controlled comparative results (75.4% and 72.4% success rates) on the MolmoSpaces benchmark.
Source: Chinese robotics — Robot learning research · Read original article ↗
English translation unavailable. Choose the original article to read it.
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
Reported success rate
94.4%
View original evidence
同一榜单、同一分组下，魔法原子自研具身智能 Agent 框架 MagicBrain 凭借 3.4B 参数规模，以 72.4%的机器人操作平均成功率位列 MolmoSpaces Combined 榜单全球第四，其抓取成功率达到 94.4%，远超行业平均水平。
Open source S3Grasp-and-place success rate
94.4%
View original evidence
其中，抓取（Pick-v1）、抓取放置（Pick & Place-v1）两项任务均拿下了所在任务榜单的全球第一，抓取任务成功率更是高达 94.4%。
Open source S23
- paper: not_reported
What remains unknown
Not established in the collected evidence: Environment, Control, Data origin.
Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
近日，在由艾伦人工智能研究所（AI2）发起的全球权威具身智能零样本评测基准 MolmoSpaces 最新榜单上，魔法原子旗下面向通用 机器人 操作的 VLM Agent 框架 EchoPolicy-0 以 75.4%的机器人操作平均成功率位列 MolmoSpaces Combined 榜单全球第一，覆盖全部 4 个 v1 任务。
Open source S2
同一榜单、同一分组下，魔法原子自研具身智能 Agent 框架 MagicBrain 凭借 3.4B 参数规模，以 72.4%的机器人操作平均成功率位列 MolmoSpaces Combined 榜单全球第四，其抓取成功率达到 94.4%，远超行业平均水平。
Open source S3
EchoPolicy-0 VLM 框架多候选轨迹选择原理 EchoPolicy-0 框架在 MolmoSpaces 的四项操作任务上完成了 3915 局全量评测，取得了 75.4% 的四项任务等权平均成功率，截至 2026 年 10 月 13 日，位列 MolmoSpaces Combined 榜单球第一。
Open source S19
EchoPolicy-0 针对具身智能模型落地场景，回答了一个问题：模型提出来的动作，怎么保证选的是对的那一个。
Open source S21
自研大脑：MagicBrain 让模型能“看见” 从“演示可用”逼近“产线可用” 具身智能 Agent 框架 MagicBrain 来自魔法原子 MagicLab Studio ，在 MolmoSpaces 的抓取、抓取放置、打开与关闭四项操作任务上， MagicBrain 完成了 3915 局全量评测，四项 v1 任务平均成功率全球第四。
Open source S22
其中，抓取（Pick-v1）、抓取放置（Pick & Place-v1）两项任务均拿下了所在任务榜单的全球第一，抓取任务成功率更是高达 94.4%。
Open source S23
Source：Chinese robotics — Robot learning research · robot.ofweek.com