Vision-Language-Action & Robotics Models
Vision-language-action models map camera input and a language instruction to robot actions. This hub catalogs the leading open VLA and robot-learning policies.
Most are research weights for use on real or simulated robots rather than browser inference, with papers and code linked on each page.
12 models for this use case
12 models available
Gemini Robotics (2025)
Google DeepMind's vision-language-action model based on Gemini 2.0. Generalist robot policy with strong dexterity.
Gemini Robotics-ER
Embodied-reasoning variant of Gemini Robotics. Enhanced 3D spatial reasoning and trajectory planning.
Google RT-2-X
Google's VLA from RT-X collaboration. Trained on Open-X-Embodiment (22 robots, 527 skills), positive transfer.
LeRobot SmolVLA
HuggingFace's 450M VLA pretrained on 487 community LeRobot datasets. Runs on consumer GPUs.
NVIDIA Cosmos-Predict-1
NVIDIA's world foundation model for physical AI. Diffusion-based video prediction for robotics simulation.
Octo Base
Berkeley/Stanford 93M transformer diffusion policy. Pretrained on 800k Open-X-Embodiment episodes.
Octo Small
Compact 27M variant of Octo. Faster inference on consumer GPUs, designed for low-latency control.
OpenVLA-7B
Stanford/Berkeley open VLA trained on 970k Open-X-Embodiment episodes. Supports LoRA fine-tuning.
Physical Intelligence Pi-0-FAST
Autoregressive π-0 variant using FAST action tokenizer. Faster inference at competitive task success.
Physical Intelligence π-0
Physical Intelligence's flagship VLA flow-matching policy. Generalist robot control, pretrained on 10k+ hrs robot data.
Physical Intelligence π-0.5
Upgraded π-0 with open-world generalization via knowledge insulation. Weights and fine-tuning open-sourced.
RDT-1B
Tsinghua's 1B diffusion-transformer bimanual manipulation policy. Predicts next 64 actions per inference.
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