Robotics

OpenVLA

The first large open vision-language-action model: a robot arm carries out commands like "put the apple in the bowl". OFT makes it several times faster.

Developer
Stanford, Berkeley and partners, USA
First release
Jun 2024
Latest release
Feb 2025
Sizes
7B
License
Commercial use allowedMIT
Running
On your own serverNeeds a GPU
Industries
Manufacturing and logistics, Science and research
Deploy on your server Hugging Face GitHub

What it does

  • Controlling a robot arm by text command
  • Pilots for robotizing simple operations
  • Base for fine-tuning to your own robot

Where it is used

ManufacturingWarehouses and logisticsResearch labs

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
no versions
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. OpenVLA-OFT
  2. OpenVLA

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can OpenVLA be used in a commercial project?

Yes. License: MIT. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does OpenVLA need?

At minimum: One GPU with 16–80 GB — mid-size versions. Without a GPU the model is not practical. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does OpenVLA support Russian?

Language does not matter for this model: it does not work with text.

Where can I download OpenVLA and what does it cost?

The OpenVLA weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

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Robot control models from Physical Intelligence: folding laundry, tidying up, handling objects. π0.5 copes better in unfamiliar settings.

DetailsRoboticsSmolVLAHugging Face · USACommercial use allowed

A small robot control model that runs on a regular laptop. Trained on open data from the LeRobot community, suited to low-cost robot arms.

Details

Source: huggingface.co/moojink/openvla-7b-oft-finetuned-libero-spatial. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.