Skip to content
Chinese robotics — Robot learning research·· 6 days agoSignalEditorial score87

MagicAtom's EchoPolicy-0 Framework Achieves Top Rank 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”

Summary

MagicAtom's EchoPolicy-0 framework achieved a 75.4% average success rate across four tasks in the MolmoSpaces benchmark, ranking first globally. MagicBrain, another framework from MagicAtom, achieved 72.4% with 94.4% pick success. Both frameworks demonstrate progress in aligning visual perception with task execution, with EchoPolicy-0 emphasizing agent scheduling and validation, and MagicBrain using visual guidance for better target alignment.

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%。
    Open source S3
  • Grasp-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%。

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 榜单全球第一。

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 · news.qq.com

Timezone · UTC

Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).