Brain
An academic open-source vision-language-action model at 7B parameters. Multi-developer collaboration across Stanford, UC Berkeley, Toyota Research Institute, and Google DeepMind. Listed here as a research-model entity; architectural details should be firmed against the OpenVLA paper at build.
Research model · Maturity: Research · Open source
Machine-readable surfaces
- Markdown mirror: /brains/openvla.md
- RSS feed: /brains/openvla/feed.xml
- JSON-LD: embedded in this page’s head
- REST API: /v1/brains/8ca71205-71ca-4036-8f26-1bb35217fa35
- Revision history: /brains/openvla/history
- Data documentation: /data
- Query this programmatically: Deploy MCP
Architecture
7B-parameter VLA. Architecture and training-data details pending firmer primary-source confirmation (OpenVLA paper at openvla.github.io and arXiv).
Key facts
- Thin-record depth note
- Architecture, parameter count, training-data composition should be firmed against the OpenVLA paper at openvla.github.io / arXiv. Entity carries verified-vs-claimed framing until firmed.
- Multi-developer collaboration
- Stanford + UC Berkeley + Toyota Research Institute + Google DeepMind (only Google DeepMind is attached as a registry developer; the academic institutions are not registry Companies)
- Powered platforms
- Research robot platforms; not a commercial-deployment brain
Developed by (1)
Common questions
What is OpenVLA?
Who developed OpenVLA?
Is OpenVLA open source?
What type of AI is OpenVLA?
What is OpenVLA's maturity stage?
Which robots run on OpenVLA?
Sources (3)
- OpenVLA project page (firm at build) · https://openvla.github.io/
- https://arxiv.org/abs/2406.09246
- https://github.com/openvla/openvla
Methodology: Verified · 3 sources (no primary) · last reviewed 2026-05-30
Verification posture
Verified
Low confidence
Review state
Stable
Last reviewed 2026-05-30
Maturity + lifecycle
Maturity stage: research
Sources by quality tier
- 1
- unclassified
- Unclassified source
- 1
- preprint
- Preprint
- 1
- code-repository
- Code repository
The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.
Methodology surface for OpenVLA.Canonical ID 8ca71205-71ca-4036-8f26-1bb35217fa35