Isaac GR00T N1.7: model ids and price

How to call it

3 ways to use Isaac GR00T N1.7, with the model id each provider expects.

Providers, model ids, endpoints and docs for Isaac GR00T N1.7
Provider	Model id	Docs
Hugging Face	`nvidia/GR00T-N1.7-3B`	Docs Model page
GitHub		github.com
Hugging Face LeRobot integration		blogs.nvidia.com

Pricing

Price not published.

No price source linked. Checked 29 September 2026.

Specs

Input: Text and images
Output: Robot actions
Context window: Not published
Max output: Not published
Open weights: Yes
Licence: NVIDIA Open Model License (weights, commercial use); Apache-2.0 (code)
Released: 17 April 2026
Status: Current
Type: Robotics model

What stands out

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

Human egocentric video pretraining

Pretrained on 20,854 hours of human egocentric video (EgoScale) across 20+ task categories, on top of robot data.

Source: huggingface.co
Scaling law for robot dexterity

First

NVIDIA reports the ‘first-ever scaling law for robot dexterity’: more human video predictably improves 22-DoF hand performance without mass teleoperation.

Source: huggingface.co
Reasoning VLA on a Cosmos backbone

3B ‘Action Cascade’ model: Cosmos-Reason2-2B VLM plus 32-layer diffusion transformer; relative end-effector action space; runs on one 16 GB+ GPU including Jetson Thor/Orin and DGX Spark.

Source: github.com

Notes

Early access with commercial licensing announced at GTC 2026-03-16; open release/HF blog 2026-04-17. Post-trained checkpoints: GR00T-N1.7-LIBERO, -DROID, -SimplerEnv-Bridge, -SimplerEnv-Fractal, GR00T-H-N1.7 (surgical-robotics variant, uploaded to HF 2026-05-30: 3B, post-trained on 601 h / ~63.9k episodes of real surgical tasks from the Open-H-Embodiment dataset across 7 platforms incl. dVRK, CMR Versius, KUKA LBR iiwa; NVIDIA Open Model License; R&D only, not for clinical use; follows the original GR00T-H announced at GTC 2026-03-16). Backbone nvidia/Cosmos-Reason2-2B is gated (accept license on HF). Validated on Unitree G1, YAM bimanual, AGIBot Genie 1. Fine-tuning: 40 GB+ GPUs recommended.