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    Figure releases Helix 2.5 for humanoid robots

    Figure says its robots began useful work in 30 rented Bay Area homes without additional training. A team member reports 56% zero-shot success with Index pretraining, versus 8% without it.

    Robert ScobleRS
    Beff (e/acc)B(
    Markus WulfmeierMW
    33 Sources, ,

    TLDR

    Figure announced Helix 2.5 on September 17, 2026, saying its robots began useful work in 30 rented Bay Area homes without additional training.

    A team member describes three full-body behaviors performed “zero-shot,” with no training data collected in any home. They say Helix 2.5 is the team's first model trained on Index. In a comparison using the same model, task-specific data and evaluation, they report 56% zero-shot success with Index pretraining, compared with 8% without it.

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    Sentiment

    Positive69.3%30.7%Negative

    Based on 134 sentiment-bearing replies from 127 accounts across 11 conversations.

    Sentiment

    Positive69.3%30.7%Negative

    Based on 134 sentiment-bearing replies from 127 accounts across 11 conversations.

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    33 Sources

    Figure@Figure_robotToday we’re releasing Helix 2.5 We rented 30 homes in the Bay Area. The robots arrived with no additional training and started doing useful work21d
    Brett Adcock@adcock_brettThe holy grail for robotics is being able to generalize: doing work in unseen places We rented 30 homes in the Bay Area and are doing tasks without any new training21d
    Corey Lynch@coreylynchIntroducing Helix 2.5 Helix 2.5 can zero-shot three full-body behaviors across 30 real homes. No training data whatsoever collected in any home. The robot just had to figure it out.21d
    Chris Paxton@chris_j_paxtonShowing generalization to 30 unseen homes and human-to-robot transfer scaling laws for humanoid robots.21d
    Robert Scoble@ScobleizerRT @Figure_robot: Today we’re releasing Helix 2.5 We rented 30 homes in the Bay Area. The robots arrived with no additional training and s…20d
    Chubby♨️@kimmonismusThe key takeaway from the new Figure03 video is that the scaling laws we know from LLMs also apply to real-world robotics using video data: the more training data there is, the better the robots perform in the real world!20d
    Axel@ax_peyone agentic robot leads another to clean up a room they communicate by voice and the lead organizes watch until the end :) funny to me how the lead repeats the follower's name, and how they self-congratulate it's one of my favorite things with agentic robots, they feel so alive20d
    Rohan Paul@rohanpaul_aiFigure just released this video. a beautiful robot future is indeed coming. Its Helix 2.5 model (Figure’s end-to-end robotics brain) lifted zero-shot household-task success more than sixfold across 30 unseen homes. Figure also reports success rising from 9% to 56%, with success requiring the entire task to be completed and no partial credit awarded.20d
    Markus Wulfmeier@m_wulfmeierZero shot results like these are why we deeply believe into the importance of post-training! How efficiently can you render any next deployment reliable is THE KEY QUESTION OF PHYSICAL AI at this moment. Enormously impressive research @Figure_robot but not deployable!20d
    Brian Roemmele@BrianRoemmeleThe Figure Home Robot is making some great leaps in ability. We have a grand and abundant future.20d

    33 Sources

    Figure@Figure_robotToday we’re releasing Helix 2.5 We rented 30 homes in the Bay Area. The robots arrived with no additional training and started doing useful work21d
    Brett Adcock@adcock_brettThe holy grail for robotics is being able to generalize: doing work in unseen places We rented 30 homes in the Bay Area and are doing tasks without any new training21d
    Corey Lynch@coreylynchIntroducing Helix 2.5 Helix 2.5 can zero-shot three full-body behaviors across 30 real homes. No training data whatsoever collected in any home. The robot just had to figure it out.21d
    Chris Paxton@chris_j_paxtonShowing generalization to 30 unseen homes and human-to-robot transfer scaling laws for humanoid robots.21d
    Robert Scoble@ScobleizerRT @Figure_robot: Today we’re releasing Helix 2.5 We rented 30 homes in the Bay Area. The robots arrived with no additional training and s…20d
    Chubby♨️@kimmonismusThe key takeaway from the new Figure03 video is that the scaling laws we know from LLMs also apply to real-world robotics using video data: the more training data there is, the better the robots perform in the real world!20d
    Axel@ax_peyone agentic robot leads another to clean up a room they communicate by voice and the lead organizes watch until the end :) funny to me how the lead repeats the follower's name, and how they self-congratulate it's one of my favorite things with agentic robots, they feel so alive20d
    Rohan Paul@rohanpaul_aiFigure just released this video. a beautiful robot future is indeed coming. Its Helix 2.5 model (Figure’s end-to-end robotics brain) lifted zero-shot household-task success more than sixfold across 30 unseen homes. Figure also reports success rising from 9% to 56%, with success requiring the entire task to be completed and no partial credit awarded.20d
    Markus Wulfmeier@m_wulfmeierZero shot results like these are why we deeply believe into the importance of post-training! How efficiently can you render any next deployment reliable is THE KEY QUESTION OF PHYSICAL AI at this moment. Enormously impressive research @Figure_robot but not deployable!20d
    Brian Roemmele@BrianRoemmeleThe Figure Home Robot is making some great leaps in ability. We have a grand and abundant future.20d