◆ Gentoo Logic · Modeling Warehouse

Architecture comparison

Covariant vs Physical Intelligence

Covariant runs closer to the foundational model (Native (own / self-hosted weights)) than Physical Intelligence (Native (own / self-hosted weights)). Shared foundation: proprietary / self-built models (highlighted).

Covariant

Robotics

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built models
Cloud · datastore
AWSobject
Compliance
SOC 2
Architecture

Warehouse robotics on RFM-1, its own robotics foundation model (team since joined Amazon).

Physical Intelligence

Robotics

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built models
Cloud · datastore
HybridObject storage (WEKA Data Platform over high-performance files/object)[2]Oracle Cloud Infrastructure storage/DB services (unspecified mix, likely OCI Object Storage and managed DB)[1]Custom distributed data infrastructure for robot learning (data pipelines between raw telemetry and training/eval)[11]
Compliance
—
Architecture

Physical Intelligence runs a proprietary robotics foundation model stack with large-scale training and data infrastructure, using WEKA for high-performance data and Oracle Cloud Infrastructure for hosted compute, complemented by Kubernetes-based CI/CD and GPU-heavy cloud environments.[1][2][7][11][12] The architecture centers on Python/C++ robotics services, PyTorch/JAX-based model training on cloud GPUs, and data pipelines from robot teleoperation and simulation into foundation model training and evaluation.[11][12]

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