OpenVLA is a research VLA with public weights and adaptation tooling, connecting visual observations and language instructions to manipulation actions.
Fine-tuning options include low-rank adaptation and full training. The repository names RLDS data pipelines and Open X-Embodiment mixtures; local task data and action normalization remain necessary integration work.
OpenVLA research team · Publication date not disclosed · Source accessed 2026-09-28
Integration and evaluation
BridgeData and LIBERO evaluation paths are documented. Scores must retain the checkpoint and benchmark protocol; the separately released OFT implementation changes training and inference.
openvla · Publication date not disclosed · Source accessed 2026-09-28
Official README inspected live. Repository code terms do not automatically cover model weights, data, or third-party assets.
License
Not publicly disclosed
Inputs, outputs & embodiment
Inputs
Not publicly disclosed
Outputs
Not publicly disclosed
Embodiment
Not publicly disclosed
Implementation & training
Compute
Not publicly disclosed
Training-data disclosures
Not publicly disclosed
Integrations
Not publicly disclosed
Reported benchmark results
Context before scores. Results from different benchmarks are not directly comparable. A simulation result does not establish real-world reliability, safety or commercial availability.
No result meets our complete revision and methodology requirements for this record yet. Inspect the original benchmark documentation before comparing published scores.
What this evidence does not establish
Model family weights are not a tested controller for every manipulator.
Pricing and deployment service terms were not verified.
Related reading is an editorial crosslink. Sourced connections describe relationships reported in the cited material. A link to a versioned profile does not establish compatibility with that version unless the connection note explicitly identifies it.