Model release

NVIDIA Isaac GR00T N1.7 3B

NVIDIA Isaac GR00T N1.7 3B is an open-weight model release in the NVIDIA Isaac GR00T N family from NVIDIA1, version N1.7 (GR00T-N1.7-3B), released Apr 17, 2026. Its weights can be downloaded by the public2 1 under the NVIDIA Open Model License Agreement1 3 6.

GR00T N1.7 is a 3B-parameter vision-language-action model from NVIDIA that maps camera images, language instructions, and robot proprioception to continuous robot actions. It replaces the earlier Eagle backbone with Cosmos-Reason2-2B and uses a flow-matching diffusion transformer as its action head. NVIDIA first released it in early access in April 2026; the repository now describes it as a general availability release.1 3 5

Model hub: Model card (Hugging Face) (external site: huggingface.co)
Repository: Isaac-GR00T repository (external site: github.com)
License: NVIDIA Open Model License (external site: nvidia.com)
Release notes: GR00T N1.7 announcement (Hugging Face blog) (external site: huggingface.co)

On AI on Hugging Face: nvidia/Cosmos-Reason2-2B, nvidia/GR00T-N1.7-3B

Last reviewedSep 29, 2026Entry updated Sep 29, 2026Documented release Apr 17, 2026

Availability and license

Overall availability

Public

Weights are downloadable from Hugging Face without an access gate under the NVIDIA Open Model License; the card states the model is ready for commercial and non-commercial use.2 1

Availability fact review: not separately recorded

Availability is separate from permission: read the license before using or redistributing.

NVIDIA Open Model License Agreement (external site: nvidia.com)1 3 6
Applies to: Weights · custom license (no SPDX identifier) · fact-level rights review not recorded
Plain-language guide to the NVIDIA Open Model License Agreement
Apache License 2.0 (Isaac-GR00T code) (external site: raw.githubusercontent.com)4 3
Applies to: Code · SPDX Apache-2.0 · on the rubric’s OSI-approved software-license list · fact-level rights review not recorded
Plain-language guide to the Apache License 2.0

The NVIDIA Open Model License allows commercial use, modification, and distribution of the model and derivatives, with NVIDIA claiming no ownership of outputs. It requires use consistent with NVIDIA's Trustworthy AI terms, a notice file with a specified NVIDIA attribution on redistribution, and indemnification of NVIDIA; rights terminate for bypassing safety guardrails or for bringing infringement litigation over the model. It is governed by U.S. and Delaware law. The README's overview also says N1.7 is licensable under Apache 2.0, but its license section and the model card assign Apache 2.0 to the code and the NVIDIA Open Model License to the weights.6 3 1

Component reuse rights

A readable or downloadable component is not automatically reusable. These indicators concern recorded license evidence, not system certification.

weights: Unknown — no complete fact-level rights review
code: Unknown — no complete fact-level rights review
data: Unknown — no complete fact-level rights review
documentation: Unknown — no complete fact-level rights review

No complete system-rights review is recorded for this release.

Model-disclosure tier

Computed from the checklist below using USASI rubric v0.2. An editorial category, not a certification.

Open-weight

The model parameters for this release can be downloaded by the public. License terms may still restrict use, redistribution, or commercial use.

The weights are under a license that is not on the rubric's OSI-approved list. Read its terms before use.

How tiers are computed

Public materials checklist

Items for a model under USASI rubric v0.2. Unknown means unassessed or insufficient evidence.

Public materials checklist for NVIDIA Isaac GR00T N1.7 3B
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Public	Base weights and several post-trained benchmark checkpoints are published on Hugging Face without an access gate.2 1
Inference codeIs code for running the model published?	Public	The Apache-2.0 Isaac-GR00T repository provides zero-shot and fine-tuned inference, a policy server, and ONNX/TensorRT export.3 4
Training codeIs the code used to train the model published?	Unknown	The repository publishes fine-tuning code (launch_finetune.py) for new embodiments; pre-training code for the base model was not found.3
Training-data informationDoes the information cover provenance, scope, acquisition, selection, labeling, processing, and where data or alternatives can be obtained? Access alone does not establish completeness.	Unknown	Not assessed.
Training-data accessCan the training data be obtained? This is independent of information completeness and reuse rights; original unshareable data need not be downloadable.	Unknown	Not assessed.
Complete training pipelineIs the complete base-training and preprocessing pipeline published, including configuration? Fine-tuning code or an inference SDK alone is insufficient.	Unknown	Not assessed.
Legacy data assessment (v0.1)Historical assessment combining download access and disclosure. Preserved for traceability; excluded from the v0.2 tier calculation. See the new separate assessments above.	Partial	The card describes the pre-training mixture at a high level (13 datasets, 21.6 million data points, human, robot, and simulated data), and NVIDIA's announcement names 20,854 hours of EgoScale human egocentric video. The full pre-training data is not documented as released.1 5
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The card points to the GR00T N1 white paper for the N1.x architecture, and the README summarizes the N1.7 changes (new backbone, relative end-effector action space, human video pre-training); a full N1.7 training configuration was not found.1 3
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Public	The README links per-benchmark guides with dataset download, fine-tuning, and evaluation commands for reproducing results on LIBERO, SimplerEnv, and SO100, plus open-loop and closed-loop evaluation tools.3

What it is useful for

The card and README describe post-training the model for a specific humanoid or other robot embodiment and task, then deploying it through a policy server, optionally with TensorRT acceleration.1 3

Run and use notes

Documented facts only. No hardware or performance claims are made without a cited source and stated assumptions.

The card lists PyTorch as the runtime and NVIDIA Ampere, Hopper, Lovelace, Blackwell, and Jetson hardware on Linux, and reports inference latency with PyTorch eager mode, torch.compile, and TensorRT on several GPUs, DGX Spark, and Jetson AGX Thor and Orin.1

Organization context

NVIDIA

Provenance and derivatives

Trained by NVIDIA. The card and README state that N1.7 uses Cosmos-Reason2-2B, an NVIDIA model with the Qwen3-VL architecture, as its vision-language backbone; Hugging Face metadata lists Qwen/Qwen3-VL-2B-Instruct (developed by the Qwen team at Alibaba Cloud) as the base model of Cosmos-Reason2-2B.1 3 7 8

Derived from: Cosmos-Reason2-2B (external site: huggingface.co) — NVIDIA vision-language backbone; no separate catalog record.
Derived from: Qwen3-VL-2B-Instruct (external site: github.com) — Base model of Cosmos-Reason2-2B per Hugging Face metadata.

Other releases in the NVIDIA Isaac GR00T N family

No other releases in this family have been assessed.

NVIDIA Isaac GR00T N family overview

What this catalog does not know

Unknown means the sources reviewed for this record do not document it. It is not evidence that something does not exist.

Training code: unknown.
Training-data information: unknown.
Training-data access: unknown.
Complete training pipeline: unknown.

Have a primary source? How to report a correction.

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S. headquarters

The model card names NVIDIA as the model developer. NVIDIA's principal executive offices are in Santa Clara, California, per its Form 10-Q for the quarter ended July 26, 2026. Its vision-language backbone derives from Qwen3-VL-2B-Instruct, recorded under provenance; that base is not U.S.-developed.1 9 7 8

Assessed Sep 29, 2026

Sources

1.
nvidia/GR00T-N1.7-3B model card (external site: huggingface.co)
NVIDIA (Hugging Face) · Model card · accessed Sep 29, 2026
2.
Hugging Face model metadata for nvidia/GR00T-N1.7-3B (external site: huggingface.co)
Hugging Face · Model card · accessed Sep 29, 2026
3.
NVIDIA/Isaac-GR00T README (external site: raw.githubusercontent.com)
NVIDIA (GitHub) · Repository · accessed Sep 29, 2026
4.
NVIDIA/Isaac-GR00T LICENSE (Apache License 2.0) (external site: raw.githubusercontent.com)
NVIDIA (GitHub) · License · accessed Sep 29, 2026
5.
NVIDIA Isaac GR00T N1.7: Open Reasoning VLA Model for Humanoid Robots (external site: huggingface.co)
NVIDIA (Hugging Face blog) · Announcement · published Apr 17, 2026 · accessed Sep 29, 2026
6.
NVIDIA Open Model License Agreement (external site: nvidia.com)
NVIDIA · License · published Oct 24, 2025 · accessed Sep 29, 2026
7.
Hugging Face model metadata for nvidia/Cosmos-Reason2-2B (external site: huggingface.co)
Hugging Face · Model card · accessed Sep 29, 2026
8.
QwenLM/Qwen3-VL (GitHub) (external site: github.com)
Qwen team (GitHub) · Repository · accessed Sep 29, 2026
9.
NVIDIA Corporation Form 10-Q for the quarter ended July 26, 2026 (external site: sec.gov)
U.S. Securities and Exchange Commission (EDGAR) · Filing · accessed Sep 29, 2026

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This listing is not an endorsement, a safety assessment, or a federal approval.

Cite this page

APA style

USASI. (2026, September 29). NVIDIA Isaac GR00T N1.7 3B. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/gr00t-n1-7-3b/

BibTeX

@misc{usasi_gr00t_n1_7_3b,
  author = {{USASI}},
  title = {NVIDIA Isaac GR00T N1.7 3B},
  year = {2026},
  month = sep,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/gr00t-n1-7-3b/}},
  note = {United States of America Superintelligence. Last updated 2026-09-29}
}

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