Foundry-VLA-1.7B-real

A 1.7B parameter vision-language-action model for bimanual robotic manipulation, part of the VLA Foundry collection. Trained on real-world manipulation data only.

Model Description

• Architecture: Foundry-VLM-1.3B vision-language backbone + (condition on last 4 layers) flow-matching diffusion action head (24 layers, 1024 hidden dim, 16 heads)
• Parameters: 1.7B (non-embedding)
• Action space: 20-dim relative actions (bimanual xyz + 6D rotation + gripper)
• Cameras: 4 views (2 scene + 2 wrist)
• Training data: 102M samples from real-world bimanual manipulation tasks only
• VLM backbone: Foundry-VLM-1.3B-200M

Evaluation Results

Success rates on 16 seen tasks and 3 unseen tasks (200 rollouts per task):

Simulator	Seen (16 tasks)	Unseen (3 tasks)
CS	1.0%	0.3%
OSS	2.2%	4.5%

Note: This model was trained on real-world data only and does not transfer well to simulation.

Usage

git clone https://github.com/TRI-ML/vla_foundry.git
cd vla_foundry
pip install -e .

from vla_foundry.models.base_model import BaseModel
model = BaseModel.from_pretrained("TRI-ML/Foundry-VLA-1.7B-real")

Links

• Project page: tri-ml.github.io/vla_foundry
• Paper: VLA Foundry (arXiv 2604.19728)
• Code: github.com/TRI-ML/vla_foundry
• Collection: VLA Foundry collection