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#Model releases
Oct 16Fri
  1. 量子位70

    Google releases Gemini 4 Argon, demo shows transfer from human video to Apptronik Apollo humanoid robot

    Google has officially opened Gemini 4 Argon to developers, enterprises, and paid subscribers worldwide; the core upgrade is stronger long-horizon task execution and multimodal capabilities. In the official demo, after watching a video of a person playing beanbag toss, Argon analyzed spatial relationships, calculated full-body joint motion, autonomously wrote simulation code, and transferred the plan to Apptronik's Apollo humanoid robot. Google says this video-to-simulation-to-reality pipeline can compress simulation modeling that previously took weeks of manual work into a few hours.

Oct 15Thu
  2. GitHub Robotics Topic41

    BrickSort v0.1.0 released: model recognizes about 600 LEGO parts

    The LEGO part recognition project BrickSort has released its first public version, v0.1.0, along with a trained model, lego_model.pt, that can recognize the type, color, category, and whether a part is printed for about 600 LEGO parts. The code is under the MIT license, and the model file uses the same license because its training data (the B200 LEGO Detection Dataset) is CC BY-SA 4.0. The author notes that the accuracy printed by training is optimistic, and an independent test on photos of unseen parts has not yet been conducted.

  3. 36Kr Embodied Intelligence61

    StepFun opens Step 5 Preview weights

    StepFun announced the official release of the Step 5 Preview weights, including BF16 and FP8 versions, along with a technical blog, supporting open-source development tools, and a deployment guide. The model weights are now available on Hugging Face and ModelScope.

Oct 14Wed
  4. Xbotics具身智能实验室 · 微信公众号66

    1.7B-parameter 3D world action model UNITAS open-sourced, surpassing 8B-parameter models on LIBERO and other benchmarks

    CrossDim Intelligence, together with The Chinese University of Hong Kong, Shenzhen, Foshan University, Sun Yat-sen University, and South China University of Technology, proposed and open-sourced UNITAS, a robot task-native 3D world action model. The code and usage instructions are publicly available in the GitHub repository DexForce/UNITAS.

  6. 甲子光年 · 微信公众号60

    Huanwang and Pyromind co-build AITV solution, raising focus recognition accuracy from 45% to 99.6%

    Huanwang Technology and Pyromind have co-built an AITV intelligent solution, performing scenario post-training on Qwen3-VL-4B. Focus recognition accuracy rose from 45% to 99.6%, the success rate of "see it, say it" reached 99%, and the success rate of "search and play" exceeded 90%. It has been deployed in "Xiaoyou Casting - Movie Search" and covers TV apps including Cloud Video Aurora, Kiwi, Mango, Youku, and Bilibili.

Oct 13Tue
  1. 银河通用机器人 · X42

    Galbot releases PASSAGE humanoid traversal framework

    The Galbot team proposes the PASSAGE framework, which combines environmental perception, whole-body motion planning, and closed-loop control so that humanoid robots can autonomously plan and execute agile traversal motions based on their surroundings. The framework was trained on 100 hours of human data covering 1,500 scenes and achieves a 98.67% success rate on the Clutter Scene Traversal benchmark.

  2. Xbotics具身智能实验室 · 微信公众号74

    UniWAM open-sources unified world and action model, leading multiple benchmarks with 99.2% on LIBERO and 68.32% on RoboTwin C2R

    The UniWAM team has open-sourced the code and weights of UniWAM, a unified world and action model, achieving success rates of 99.2%, 92.6%, and 68.32% on LIBERO, LIBERO-Plus, and RoboTwin 2.0 C2R, respectively, the highest values among the methods listed in the corresponding tables of the paper.

  3. 深圳市机器人协会 · 微信公众号70

    HKU MMLAB releases PhysicalRSI 1.0, tops RoboDojo and sharply cuts token costs

    The University of Hong Kong's MMLAB jointly released PhysicalRSI 1.0, a self-evolving embodied intelligence system baseline, achieving a score of 36.27 and an average task success rate of 31.38% on RoboDojo, ranking first.

    Why it matters: The material provides the specific mechanisms of the self-evolving baseline and comparison data with general large models, allowing readers to understand the causes of shortcomings in precision manipulation and paths for improvement.

  4. ZhenFund · 微信公众号63

    Natural Will releases first physical general foundation model Natura-1, 50-billion-parameter MoE drives 20-DoF dexterous hand

    Natural Will has released Natura-1, its first general foundation model for the physical world. It is a 50-billion-parameter mixture-of-experts (MoE) model pretrained on 1 million hours of first-person human experience data. Taking language and vision as input, it can drive a 20-DoF dexterous hand within a 100-millisecond control loop and follow complex natural-language instructions zero-shot.

  5. Dexmal 原力灵机 · 微信公众号56

    Force Machine DM0.5 showcases three task types at the CIIF: connector insertion quality inspection, industrial insertion, and flexible cutting

    Force Machine presented its self-developed DM0.5 general-purpose embodied brain at the AXERA booth at the 2026 China International Industry Fair, completing three task types: connector insertion quality inspection, Insert Anything general-purpose industrial insertion, and dexterous-hand flexible cutting, with model inference performed on the AXERA high-compute platform.

Oct 12Mon
  2. Shanghai AI Laboratory - Embodied Intelligence73

    Shanghai AI Lab launches decision model Intern·Mingjue, outperforming Jev and releasing 0.8B, 2B, and 4B weights

    Shanghai AI Laboratory has launched the decision model Intern·Mingjue (Decision), which outperforms Jev and is available in 0.8B, 2B, and 4B parameter versions. In RTX 4090 tests, the 0.8B and 2B models had an average end-to-end latency of about 33 milliseconds and about 30 decisions per second, while the 4B model was 44.16 milliseconds and Jev was 109.70 milliseconds.

    Why it matters: The original text provides measured latency, benchmark scores, and a mechanism for routing between large and small models, which readers can use to judge the decision model's suitability for interactive scenarios.

Oct 10Sat
Sep 30Wed
  3. 北京智在无界科技有限公司58

    Being-H0.7 from ZhiZaiWuJie accepted to NeurIPS 2026, Being-H series completes ICML, CoRL, and NeurIPS acceptances within one year

    Being-H0.7, the general-purpose dexterous manipulation large model independently developed by ZhiZaiWuJie, has been accepted to NeurIPS 2026, marking the Being-H series' completion of acceptances to the three top conferences ICML, CoRL, and NeurIPS within one year.

Sep 28Mon
  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.

  2. PsiBot/灵初智能66

    Lingchu Intelligence releases Psi-R2.5, using strong Pair Data to solve human-machine data alignment challenges

    Lingchu Intelligence has officially released its embodied model Psi-R2.5, which uses a two-tier architecture with a QwenVL3.5-4B high-level planner plus a Wan2.2-IT2V-5B low-level controller, and proposes the strong Pair Data standard. The model reverse-invokes the Psi-W0 world model to generate human demonstration videos backward from real-robot data, enabling mass production of paired data, and supports in-context learning (ICL) for zero-shot generalization to new tasks. It comes with a HIL+RL post-training framework and is claimed to raise task success rates to 99% after a few iterations taking only 1-2 working days, and has already been deployed at customer sites.

    Why it matters: The original article details the model architecture, the strong Pair Data data standard, and the reverse-generation method, letting readers understand how its data approach supports real-robot generalization.

Sep 24Thu
  3. 尚颀资本 · 微信公众号28

    Shangqi Weekly | Ecosystem Together · News at a Glance

    Shangqi Capital released its weekly newsletter summarizing recent developments at ecosystem companies: Yixing Intelligence completed a new funding round of nearly 2 billion yuan, with a post-investment valuation of nearly 15 billion yuan, and its first-generation Epoch compute chip has entered mass production and delivery; Infinigence AI, together with Tsinghua University and Shanghai Jiao Tong University, open-sourced APXInf, an on-device inference engine for embodied intelligence, supporting platforms such as RTX 4090, Jetson Orin, and Jetson Thor; the first embodied tennis robot jointly developed by LimX Dynamics and Yinghansi Dynamics made its debut at the "Billie Jean King" Cup finals on September 22.

Sep 23Wed
Sep 21Mon
  2. AgiBot49

    AGIBOT demonstrates WITA-Omni real-time human-robot interaction at Greater Bay Area Film Concert

    At the Greater Bay Area Film Concert, AGIBOT used the WITA-Omni omni-modal embodied model to achieve real-machine human-robot interaction; the robot can identify its conversation partner, judge the right timing to respond, and coordinate speech, motion, and facial expressions in real time. The model uses a Thinker-Talker-Actor architecture, and WITA-Omni Preview ranked first on the DailyOmni benchmark with an average accuracy of 85.21%, leading in six of eight evaluation dimensions.

Sep 20Sun
  1. PsiBot/灵初智能73

    Psi Robotics Releases Psi-R2.5 Model: Scaling Human Data for Embodied Intelligence with Strong Pair Data

    Psi Robotics released the Psi-R25 robot manipulation model. Its core upgrades are improved data quality and data attribute compression: it reviewed and extracted high-quality data from 100,000 hours of data, and used strong pair data to align human data with robot data.

    Why it matters: The original article details how strong pair data is generated and the data quality standards, giving readers a referenceable path for aligning human data to robot data.

Sep 18Fri
Sep 17Thu
  1. Figure AI79

    Figure AI releases Helix 2.5, achieving zero-shot full-body autonomy in 30 unfamiliar homes

    Figure AI released Helix 2.5, which completed three long-horizon full-body behaviors—tidying a living room, folding towels, and making a bed—zero-shot in 30 Bay Area homes where no data had ever been collected, without collecting data or fine-tuning in the evaluation environments.

    Why it matters: The original article provides controlled comparison data on Index pretraining for zero-shot generalization and evaluation details, helping readers understand the actual level of humanoid robot pretraining transfer.

Sep 16Wed
  1. Shanghai AI Laboratory - Embodied Intelligence71

    2026 Pujiang Innovation Forum AI-Enabled Scientific Research Special Forum Held; Shanghai AI Lab Releases ShuSheng-S2 and ShuSheng World Model W0

    The 2026 Pujiang Innovation Forum AI-Enabled Scientific Research Special Forum was held on September 13 at the Shanghai Zhangjiang Science Hall, co-hosted by the Fourth Department of the Ministry of Science and Technology and Shanghai AI Lab. During the forum, Shanghai AI Lab launched the ShuSheng Scientific Multimodal Large Model S2 and the ShuSheng Physical World Model W0, opened the full-stack services of the ShuSheng·DuanYan Scientific Discovery Platform, and jointly released 20 major scientific questions with 14 institutions as well as multiple co-construction achievements of the "Climber Program."

    Why it matters: The official report summarizes multiple advances released at the forum, among which the force-touch fusion and robotic arm operation details of the W0 world model may be of reference to readers in the embodied direction.

Sep 15Tue
  1. OFweek Robotics45

    EBKernel releases brain-inspired cognitive world model Cog-WM 1.0, exploring a new "root technology" path for China's embodied intelligence

    EBKernel released its brain-inspired cognitive world model Cog-WM 1.0 on September 14 at the Brain-Inspired Embodied Intelligence sub-forum of the Shanghai Pujiang Innovation Forum. It includes a navigation branch, Cog-WM Nav 1.0, and a manipulation branch, Cog-WM Manip 1.0, and uses memory, prediction, and active exploration to help robots understand the physical world.

  2. New Strategy Robotics54

    JoyIn releases Aether embodied intelligence model and questions OpenAI distillation

    On September 10, 2026, Suzhou-based JoyIn released the Aether embodied intelligence model, aimed at humanoid robot body control and real-world task execution. JoyIn says the model was trained on about 200 hours of human video and zero real-machine data, has roughly 4 billion parameters, exceeds 90% success rate on first attempts at some tasks, can run on bodies from Unitree Robotics, AgiBot and others, and that it plans to partially open up the model's capabilities.

  3. 小鹏机器人66

    XPeng XOS 6.3.0 OTA Deploys Second-Generation VLA Upgrade, Adds InfiniVLA and X-Foresight World Model

    XPeng XOS 6.3.0 deploys a second-generation VLA upgrade via OTA, restructuring the model architecture around the time dimension: InfiniVLA lets historical visual information continuously participate in current judgments, with the vehicle side selecting 30 seconds of historical context alongside streaming autoregressive inference.

    Why it matters: The article explains concretely the trade-offs in co-designing model architecture and deployment under onboard compute constraints, making it a useful engineering reference for deploying large models on limited hardware.

  4. Chelsea Finn56

    OM-1 Releases First Robot Foundation Model, Zero-Shot Generalizes to Desktop Arms, Industrial Arms, and Humanoid Robots

    OM-1 has released its first robot foundation model, which can zero-shot generalize to desktop robotic arms, industrial robotic arms, and humanoid robots. The model learns directly from human operation data without using teleoperation or robot data, claims near-human-level dexterity and efficiency, and supports multi-robot collaboration. Chelsea Finn reposted and congratulated the relevant authors on the release.

Sep 14Mon