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    You are at:Home»Technology»Hugging Face says its new robotics model is so efficient it can run on a MacBook
    Technology

    Hugging Face says its new robotics model is so efficient it can run on a MacBook

    Earth & BeyondBy Earth & BeyondJune 4, 2025003 Mins Read
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    Hugging Face says its new robotics model is so efficient it can run on a MacBook
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    It’s becoming a little easier to build sophisticated robotics projects at home.

    AI dev platform Hugging Face released earlier this week an open AI model for robotics called SmolVLA. Trained on “compatibly licensed,” community-shared datasets, SmolVLA outperforms much larger models for robotics in both virtual and real-world environments, Hugging Face claims.

    “SmolVLA aims to democratize access to vision-language-action [VLA] models and accelerate research toward generalist robotic agents,” writes Hugging Face in a blog post. “SmolVLA is not only a lightweight yet capable model, but also a method for training and evaluating generalist robotics [technologies].”

    SmolVLA is a part of Hugging Face’s rapidly expanding effort to establish an ecosystem of low-cost robotics hardware and software. Last year, the company launched LeRobot, a collection of robotics-focused models, datasets, and tools. More recently, Hugging Face acquired Pollen Robotics, a robotics startup based in France, and unveiled several inexpensive robotics systems, including humanoids, for purchase.

    SmolVLA, which is 450 million parameters in size, was trained on data from LeRobot Community Datasets, specially-marked robotics datasets shared on Hugging Face’s AI development platform. Parameters, sometimes referred to as weights, are the internal components of a model that guide its behavior.

    Hugging Face claims that SmolVLA is small enough to run on a single consumer GPU — or even a MacBook — and can be tested and deployed on “affordable” hardware, including the company’s own robotics systems.

    In an interesting twist, SmolVLA also supports an “asynchronous inference stack,” which Hugging Face says allows the model to separate the processing of a robot’s actions from the processing of what it sees and hears. As the company explains in its blog post, “[b]ecause of this separation, robots can respond more quickly in fast-changing environments.”

    SmolVLA is available for download from Hugging Face. Already, a user on X claims to have used the model to control a third-party robotic arm:

    🚀 SmolVLA — feels like a BERT moment for robotics 🤖
    I tried it on the Koch Arm:
    Inference on RTX 2050 (4GB), fine-tuned with just 31 demos, and matches/outperforms single-task baselines 🔥

    Big thanks to @RemiCadene @danaubakirova @mustash97 @francesco__capu 🙌 pic.twitter.com/TiBkAZGwkM

    — Xingdong Zuo (@XingdongZ) June 4, 2025

    It’s worth noting that Hugging Face is far from the only player in the nascent open robotics race.

    Nvidia has a collection of tools for open robotics, and startup K-Scale Labs is building the components for what it’s calling “open-source humanoids.” Other formidable firms in the segment include Dyna Robotics, Jeff Bezos-backed Physical Intelligence, and RLWRLD.

    efficient face Hugging MacBook model Robotics Run
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