---
title: LabVLA
emoji: 🧪
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: 6.15.1
app_file: app.py
short_description: VLA model for scientific laboratory robotics
python_version: "3.12"
startup_duration_timeout: 1h
---

# LabVLA: Vision-Language-Action Model for Scientific Laboratories

LabVLA is the first VLA foundation model designed specifically for scientific laboratory environments.
It combines a **Qwen3-VL-4B** vision-language backbone with a **DiT flow-matching action expert** trained
with the π0.5 recipe: FAST action-token pre-training → flow-matching post-training with knowledge isolation.

This demo lets you provide a laboratory camera view and a natural language instruction, and the model
predicts a chunk of 50 future robot actions (7 arm joint angles + 1 gripper width per step) for a Franka
Panda manipulator.

## Model

- **Model**: [zjunlp/LabVLA-5B-Base](https://huggingface.co/zjunlp/LabVLA-5B-Base)
- **Paper**: [LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories](https://huggingface.co/papers/2606.13578)
- **GitHub**: [zjunlp/LabVLA](https://github.com/zjunlp/LabVLA)

## Inputs

- **Camera View**: An image of the laboratory workspace
- **Task Instruction**: Natural language instruction (e.g., "Pick up the beaker")
- **Robot State**: 7 arm joint angles + 1 gripper width (Franka Panda 7-DOF)

## Outputs

- **Action Trajectory**: 50-step predicted action chunk visualized as per-joint trajectory plots
- **Action Details**: JSON with the raw action values and timing information