pi0.5
Physical Intelligence
A VLA model designed for open-world generalization by combining heterogeneous robot data, semantic subtask prediction, and high-level knowledge transfer.
- Code
- Not listed
- Weights
- Not listed
- Checkpoint
- Not listed
- License
- Unverified
Decision summary
Open-world generalization
Hardware, latency, dependencies, and checkpoint loading are not pipeline-tested.
Verify repository and artifact licenses.
Evidence profile
A visual read of adoption evidence. Scores describe catalog evidence readiness, not task performance.
Published evaluation
1/6
dimensions scored
Unknown evidence remains visible and is never treated as a zero.
Why these scores
The strongest decision reasons behind the evidence profile.
Artifact availability
UnknownCode and weights are not verified.
Training and loading reproducibility
UnknownNo verified loading configuration is available.
Evaluation evidence
UnknownNo structured evaluation evidence has been verified.
Data requirements
Declared loop-data needs, missing evidence, and the next checks that matter.
Observation / ego video
observation
Language intent / task phase
language intent · task phase
Action / robot state
actions · robot state
Future state / dynamics
Descriptive model record
Critical gaps
Core categories are represented. Interface alignment and data quality still require verification.
Linked datasets
Signal-level links only. Verify runtime interfaces before use.
More evidenceShowHide
Additional data signals
Sim-real / embodiment metadata
robot state
Additional decision dimensions
License or access terms are not verified.
— · c20Required signal categories are structured; exact tensor and action interfaces still need verification.
76 · c70Hardware, latency, dependencies, and checkpoint loading are not pipeline-tested.
— · c10Artifact facts
- release_year
- official_claim
- 2025
- curated official source year
- model.required_signals
- official_claim
- observation · language intent · task phase · actions · robot state
- Official model documentation and curated signal mapping
- release_timing
- official_claim
- 2025
- Official model project or paper year
- discovery.source
- secondary_claim
- name: worldbench/awesome-embodied-data-pyramid · trust: discovery_only · revision: 0568599d0619f20946e8089f6a941d0d9e30b690
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- discovery.raw_fields
- secondary_claim
- Time: 2025.4 · Method: π0.5 · Institution: Physical Intelligence · Project: [](https://www.pi.website/blog/pi05) · Model: VLA · Data: ![Real][data-real] ![General][data-general]
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- model.reported_release_time
- secondary_claim
- 2025.4
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- model.type
- secondary_claim
- VLA
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- model.training_data_layers
- secondary_claim
- real_robot · general
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- model.institution
- secondary_claim
- Physical Intelligence
- #table-embodied-foundation-models-vla-wam, table 17, row 16
- catalog.curation
- secondary_claim
- tier: editorial_focus · collection: WorldBench Awesome Embodied Data Pyramid · policy: human_curated_priority
- #table-embodied-foundation-models-vla-wam, table 17, row 16
Additional references
OpenBot notes
- A useful anchor for Catalog fields around task phase and heterogeneous data mixtures.