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Only Models#Open source
  1. OFweek Robotics82

    X-Era AI Tuoyuan Zhihui releases open-source 4D world action model E0.5, with out-of-distribution real-robot success rate surpassing π0.5

    X-Era AI Tuoyuan Zhihui released the open-source native 4D world action model E0.5, which uses a 3D foundation model as its backbone and integrates future 3D geometry prediction directly into action learning. On the AgileX Piper dual-arm robot and the Zerith H1 humanoid robot, after pretraining on about 160,000 robot trajectories, E0.5 achieved overall average success rates of 85.0% and 88.3%, respectively, improving on π0.5 by 13.3 and 26.7 percentage points; its out-of-distribution average success rates were 73.3% and 76.7%.

    Why it matters: The original text provides a comparison of E0.5 and π0.5 success rates on out-of-distribution real-robot tasks, which readers can use to judge the effect of 3D geometry supervision on manipulation generalization.

  1. 至简动力 · 微信公众号72

    Simplexity Robotics releases and open-sources world-action model SimpleWAM, with 6B model achieving on-device inference as low as 42.31ms

    Simplexity Robotics has launched and open-sourced the world-action model SimpleWAM; the 6B-parameter version reduces inference latency on NVIDIA ThorX (T5000) from 181.23ms to 42.31ms, enabling high-frequency closed-loop operation on-device at nearly 24Hz.

    Why it matters: The original article presents the on-device optimization path from 181ms to 42ms and four architectural designs, which can be transferred to understand how world-action models can meet high-frequency closed-loop control requirements.

  1. Dexmal 原力灵机 · 微信公众号73

    Force Spirit DM0.5 Tops All Four RoboColiseum Leaderboards

    Force Spirit announced that DM0.5 has topped all four RoboColiseum leaderboards (instruction following, spatial understanding, perturbation adaptation, and general manipulation), making it the only model on the leaderboards to rank first in every evaluation.

    Why it matters: The original article lists DM0.5's specific scores on multiple leaderboards and its inference latency reduction data, which can be used to assess the practical effectiveness of its pretraining approach.

  1. 智源研究院 · 微信公众号72

    Zhongzhi FlagOS completes Day0 adaptation of Qwen3.8-2.4T across nine chips

    On the first day of Alibaba's open-source release of the 2.4-trillion-parameter MoE model Qwen3.8-2.4T-A95B, the Zhongzhi FlagOS community completed multi-chip adaptation, precision alignment, and deployment validation across 9 AI chips, providing BF16, FP8, INT8, and other multi-precision versions.

    Why it matters: The article presents a zero-code-change adaptation path and a quantization compression scheme, which readers can use to assess how existing domestic compute can support ultra-large models.

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