Robotics

SmolVLA

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.

Developer
Hugging Face, USA
First release
Jun 2025
Latest release
Jun 2025
Sizes
450M
License
Commercial use allowedApache 2.0
Running
On your own serverAlso runs without a GPU
Industries
Manufacturing and logistics, Science and research, Education
Deploy on your server Hugging Face GitHub

What it does

  • Controlling a low-cost robot arm
  • Quick robotization pilots and demos
  • Training staff and students

Where it is used

Small-scale manufacturingEducationRobotics startups

Hardware requirements

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

Versions

  1. SmolVLA

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 SmolVLA be used in a commercial project?

Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does SmolVLA need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does SmolVLA support Russian?

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

Where can I download SmolVLA and what does it cost?

The SmolVLA 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.

Similar models

RoboticsOpenVLAStanford, Berkeley and partners · USACommercial use allowed

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.

DetailsRoboticsπ0 / π0.5 (openpi)Physical Intelligence · USACommercial use with conditions

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

Details

Source: huggingface.co/lerobot/smolvla_base. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.