Octo
Octo Model Team
Open-source generalist robot policy pretrained on Open X-Embodiment trajectories and designed for fine-tuning to new robots and tasks.
Fine-tuning to new observation spaces
Good bridge between pure policy learning and broader VLA/WAM framing.
A model hub link is a declaration. Files, loadability, evaluation, and deployment are scored separately.
Model decision scorecard
Use-case scores and evidence confidence are separate; Unknown is not treated as failure.
Code, weights, and checkpoints
UsefulAn official model hub is linked; weight files and loadability are not verified.
Loading and training reproducibility
UnknownNo verified loading configuration is available.
Training data requirements
UsefulRequired signal categories are declared; exact tensor and action interfaces still need verification.
Evaluation evidence
UsefulEvaluation focus is declared, but metrics are not independently verified.
Deployment readiness
UnknownHardware, latency, dependencies, and runtime loading are not yet verified.
Artifact facts and provenance
No metadata-verified artifact facts yet. Source links remain declarations only.
Loop signal demand
Signals this model family needs for training, evaluation, or failure mining.
Observation / ego video
observation · goal image · Robot trajectories with observations and actions · Flexible task definitions such as language or goal images
Language intent / task phase
language intent · goal image · Flexible task definitions such as language or goal images · Cross-platform task success
Action / robot state
actions · robot state · Robot trajectories with observations and actions · Sensor/action-space metadata for adaptation
Future state / dynamics
Needs future-state supervision or rollout structure to validate predictive dynamics.
Feedback / correction / failure
Cross-platform task success
Sim-real / embodiment metadata
robot state · Robot trajectories with observations and actions
Evaluation focus
- Fine-tuning to new observation spaces
- Action-space transfer
- Cross-platform task success
Missing critical loop signals
Core signal demands are represented. Check quality, alignment, and access constraints.
Related catalog datasets
EgoWorld
Bimanual manipulation in LeRobot format
Dataset license restricts commercial use.
Egocentric Adjust Bottle
Apache-2.0 LeRobot bottle-adjustment task
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
EgoStation GoPro Pick-and-Place
GoPro first-person pick-and-place trajectories
Dataset license restricts commercial use.
OpenBot notes
- Good bridge between pure policy learning and broader VLA/WAM framing.
- OpenBot can help decide whether a dataset has enough action/state structure for Octo-style fine-tuning.