aid: physical-intelligence
name: Physical Intelligence
description: >-
  Physical Intelligence (often styled "Pi" or "π") is a San Francisco-based
  research company building general-purpose foundation models for robotics
  with the stated goal of producing learning algorithms that can control any
  robot to do any task. The company has published a continuing line of
  Vision-Language-Action (VLA) models: π0 (October 2024, first generalist
  multi-task multi-robot policy), π0-FAST (autoregressive variant via Real-time
  Action Chunking / FAST tokenization), π0.5 (April 2025, open-world
  generalization), π*0.6 (November 2025, reinforcement-learning from
  experience), and π0.7 (April 2026, steerable model with emergent
  capabilities). Physical Intelligence releases significant work as open
  source: the openpi repository (~12K stars) is the canonical home for π0
  weights and code, with companion repos including real-time-chunking-kinetix,
  pi-data-sharing, aloha, augmax, and rlds_dataset_builder. The company does
  not yet offer a hosted commercial API; access to the platform is via
  open-weight models and research collaborations.
type: Index
position: Provider
access: 3rd-Party
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
tags:
  - Robotics
  - Foundation Models
  - Vision Language Action
  - Embodied AI
  - Reinforcement Learning
  - Imitation Learning
  - Open Source
  - Open Weights
  - pi0
  - openpi
  - Manipulation
  - Generalist Policy
url: https://raw.githubusercontent.com/api-evangelist/physical-intelligence/refs/heads/main/apis.yml
created: '2026-05-23'
modified: '2026-05-23'
specificationVersion: '0.20'
apis: []
common:
  - type: DomainSecurity
    url: security/physical-intelligence-domain-security.yml
  - type: Website
    url: https://www.physicalintelligence.company
  - type: AlternateWebsite
    url: https://www.pi.website
  - type: Blog
    url: https://www.pi.website/blog
  - type: Research
    url: https://www.pi.website/research
  - type: GitHubOrganization
    url: https://github.com/Physical-Intelligence
  - type: OpenPi
    url: https://github.com/Physical-Intelligence/openpi
  - type: Careers
    url: https://www.pi.website/careers
  - type: Twitter
    url: https://twitter.com/physical_int
  - type: LinkedIn
    url: https://www.linkedin.com/company/physical-intelligence
maintainers:
  - FN: Kin Lane
    email: kin@apievangelist.com