A compact 450M-parameter VLA from Hugging Face, pretrained on community-collected LeRobot datasets and sized for fine-tuning and inference on consumer GPUs.
lerobot/pi0fast-base
Indexed from Hugging FaceLinked to its home on Hugging Face. FrontierOS indexes it; nothing is hosted or mirrored here.ModelVision-language-action2.9B paramsEst. 24 GB GPUEstimated minimum compute for inference: Desktop GPU with about 24 GB of memory. Not a benchmark.Gemma termsSingle armBimanual
About
An autoregressive pi0 variant that predicts actions as compressed FAST tokens from a DCT-based tokenizer instead of using flow matching, packaged for LeRobot.
Why it matters for physical AI
FAST tokenization shortens VLA training on high-frequency, dexterous control data, which matters when compute is limited.
Summary written by FrontierOS in our own words. The upstream card and license govern use. Metadata checked 27 Sep 2026. Read the full card on Hugging Face
Files, weights and version history live on Hugging Face. FrontierOS indexes this repo; it does not host or mirror it.
hf download lerobot/pi0fast-baseUses the Hugging Face CLI (pip install -U huggingface_hub). This downloads the whole repo; add --include "<pattern>" to fetch only the files you need.
pi0, pi0-FAST or pi0.5: which base do you fine-tune first?
LeRobot now ships ports of three Physical Intelligence checkpoints. pi0 uses flow matching, pi0-FAST predicts compressed action tokens, and pi0.5 adds co-training aimed at unfamiliar scenes.
More vision-language-action
Browse allLeRobot's port of the Physical Intelligence pi0.5 base model, which is co-trained on web and multi-robot data to generalize better to unfamiliar homes and objects.
A 3B cross-embodiment robot foundation model from NVIDIA that combines a vision-language backbone with a diffusion-transformer action head and can be post-trained on a new robot with a modest amount of data.