Post-Cutoff

Boston DynamicsLarge Behavior Models (TRI) familyCurrentRobotics modelReleased 20 Aug 2025

Atlas Large Behavior Model (Boston Dynamics + TRI LBM)

PricePrice not published

Where it stands

23newer robotics models since its release

The 5 newest are listed. All robotics models

Weights
Closed weights.

How to call it

2 ways to use Atlas Large Behavior Model (Boston Dynamics + TRI LBM).

Providers, model ids, endpoints and docs for Atlas Large Behavior Model (Boston Dynamics + TRI LBM)
ProviderModel idEndpointDocs
Not available (internal research policy for Atlas) bostondynamics.com
TRI LBM Eval (open simulation benchmark, not the model) github.com

Pricing

Price not published.

No price source linked.

Specs

Input
Images and text
Output
Robot actions
Context window
Not published
Max output
Not published
Open weights
No
Licence
Proprietary
Released
20 August 2025
Status
Current
Type
Robotics model

What stands out

What its maker marketed at launch, and what people found later, each with its source.

  • One language-conditioned policy for whole-body loco-manipulation

    A single end-to-end policy maps images, proprioception and language to actions for the full 50-DoF Atlas at 30 Hz, combining stepping, crouching and center-of-mass shifts with dexterous manipulation in long-horizon tasks, replacing separate walking and manipulation controllers.

    Source: bostondynamics.com

  • Diffusion Transformer with flow matching

    450M-parameter Diffusion Transformer trained with a flow-matching objective, predicting 48-step action chunks (1.6 s); trained on Atlas teleop data, the Atlas Manipulation Test Stand, TRI’s Ramen dataset and simulation co-training.

    Source: bostondynamics.com

  • Inference-time speed-up

    Policies can run 1.5-2x faster than the human demos at inference time without retraining by rescaling action timing.

    Source: bostondynamics.com

  • Pretraining cuts task data by up to 80%

    TRI’s LBM study (~1,700 h of robot data, 1,800 real and 47,000+ sim rollouts) found pretrained LBMs need up to 80% less task-specific data.

    Source: toyotaresearchinstitute.github.io

Notes

Research collaboration announced Aug 2025 (Toyota release: https://newsroom.toyota.eu/ai-powered-robot-by-boston-dynamics-and-toyota-research-institute-takes-a-key-step-towards-general-purpose-humanoids/). The production electric Atlas (CES 2026) also integrates Google DeepMind foundation models (Gemini Robotics); Hyundai trains Atlas on parts logistics at its Georgia RMAC (2026-09-22). No public weights or API for the Atlas LBM. Exact announcement day (2025-08-20) is from press coverage dated 2025-08-20/21.