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Organization

Physical Intelligence

Physical Intelligence is an AI model developer and research lab headquartered in San Francisco, California324. This catalog lists 1 software project from Physical Intelligence, under licenses including the Apache License 2.0.

Documented roles: Model developer · Research lab · Robotics

Physical Intelligence develops foundation models for robot control, including the π0, π0-FAST, and π0.5 vision-language-action models. It publishes code and checkpoints for these models in its openpi repository.12

Last reviewedEntry updated

Using this organization’s offerings

Ownership, delivery, and openness answer different questions. Publicly traded does not mean open source; privately held does not mean closed.

The detailed audience, self-hosting, pricing, and restrictions review has not yet been completed. Consult the sourced product records below and the publisher’s current terms. Missing detail means unknown, not unavailable.

Key facts

Ownership (separate from openness)
Privately held

Recorded classification; fact-level ownership verification pending.

Legal form
Unknown
Headquarters
San Francisco, California324
Founded
Unknown
Sectors
Robotics, Open models, Research

What is and isn’t public

An evidence-based summary of what this catalog has documented. It is not a verdict on the organization as a whole.

Physical Intelligence publishes code under Apache 2.0 and downloadable checkpoints for π0, π0-FAST, and π0.5 in the openpi repository. The π0 paper describes the internal robot data used for pre-training; this catalog found no public release of that data. This record does not assess whether the company's other models are public.12

Products

Documented products and how they are delivered. Each row links to the official page.

No product records yet.

Cataloged artifacts

Records in the Open Models & Tools directory that list this organization as a maintainer or publisher.

Research stacks (1)

  • openpiSoftwareAvailability: Public

What this catalog does not know

Unknown means the sources reviewed for this record do not document it. It is not evidence that something does not exist.
  • Legal name: not documented in the sources reviewed for this record.
  • Founding date: not documented in the sources reviewed.
  • Products: none documented in this record.

Have a primary source? How to report a correction.

U.S. eligibility

How this record meets the catalog’s published eligibility policy.

Eligible · basis: U.S. headquarters

TechCrunch (January 2026) reports on the company's headquarters in San Francisco, and the π0 paper lists the authors' affiliation as Physical Intelligence, San Francisco, California, USA. The Robot Report also describes it as San Francisco-based. The company's own website could not be fetched for this review; its job board lists roles in San Francisco and Fremont, California.3245

Assessed Sep 29, 2026

Eligibility policy

Sources

  1. 1.
    Physical-Intelligence/openpi (external site: github.com)

    Physical Intelligence · Repository · accessed Sep 29, 2026

  2. 2.
    π0: A Vision-Language-Action Flow Model for General Robot Control (external site: arxiv.org)

    arXiv · Paper · published Oct 31, 2024 · accessed Sep 29, 2026

  3. 3.
  4. 4.
    Physical Intelligence open-sources Pi0 robotics foundation model (external site: therobotreport.com)

    The Robot Report · News report · published Feb 7, 2025 · accessed Sep 29, 2026

  5. 5.
    Physical Intelligence job board (Ashby posting API) (external site: api.ashbyhq.com)

    Physical Intelligence (Ashby) · Other · accessed Sep 29, 2026

  6. 6.
    Official careers page (Join us) with embedded job board (external site: pi.website)

    Physical Intelligence · Official page · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

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Cite this page

APA style

USASI. (2026, October 1). Physical Intelligence. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/companies/physical-intelligence/

BibTeX

@misc{usasi_physical_intelligence,
  author = {{USASI}},
  title = {Physical Intelligence},
  year = {2026},
  month = oct,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/companies/physical-intelligence/}},
  note = {United States of America Superintelligence. Last updated 2026-10-01}
}

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