Brain
Galbot's grasping foundation model, GraspVLA (launched Jan 2025): an end-to-end Vision-Language-Action model pre-trained on SynGrasp-1B, a billion-frame synthetic grasping dataset with photorealistic rendering and domain randomization. Enables zero-shot generalization to new grasping tasks without additional training, powering dexterous manipulation on Galbot's robots.
Foundation model · Maturity: Research · Closed · Powers 1 robot
Machine-readable surfaces
- Markdown mirror: /brains/graspvla.md
- RSS feed: /brains/graspvla/feed.xml
- JSON-LD: embedded in this page’s head
- REST API: /v1/brains/6ab6bd66-6794-4509-bb25-12479104d5a2
- Revision history: /brains/graspvla/history
- Data documentation: /data
- Query this programmatically: Deploy MCP
Key facts
- Model type
- Vision-Language-Action model
- Maturity stage
- research
- Open source
- no
- Training data
- SynGrasp-1B, a billion-frame synthetic grasping dataset with photorealistic rendering and domain randomization
- Architecture
- end-to-end Vision-Language-Action model
Developed by (1)
Powers (1)
Where GraspVLA (Galbot) runs
View the global mapDeployments of robots powered by GraspVLA (Galbot), by place and type.
Common questions
What is GraspVLA (Galbot)?
Which robots run on GraspVLA (Galbot)?
Who developed GraspVLA (Galbot)?
Is GraspVLA (Galbot) open source?
What type of AI is GraspVLA (Galbot)?
What is GraspVLA (Galbot)'s maturity stage?
Sources (2)
Methodology: Verified · 2 sources (no primary) · last reviewed 2026-06-28
Verification posture
Verified
Low confidence
Review state
Stable
Last reviewed 2026-06-28
Maturity + lifecycle
Maturity stage: research
Sources by quality tier
- 1
- preprint
- Preprint
- 1
- unclassified
- Unclassified source
The framework is documented at /methodology. Corrections at /corrections. Reviewer: DEPLOY editorial team.
Methodology surface for GraspVLA (Galbot).Canonical ID 6ab6bd66-6794-4509-bb25-12479104d5a2