NVIDIA Cosmos3-Nano
NVIDIA Cosmos3-Nano is an open-weight model release in the NVIDIA Cosmos family from NVIDIA1, version Cosmos3-Nano (16B), released May 31, 2026. Its weights can be downloaded by the public21 under the OpenMDW License Agreement, version 1.1 (OpenMDW-1.1)123.
Cosmos3-Nano is the 16B-parameter model in NVIDIA's Cosmos 3 family, released on May 31, 2026. It shares the family's mixture-of-transformers design, generating text autoregressively and images, video, audio, and robot actions by diffusion, from combinations of text, image, video, audio, and action-trajectory inputs.19
- Model hub: Model card (Hugging Face) (external site: huggingface.co)
- License: OpenMDW License 1.1 (external site: openmdw.ai)
- Repository: Cosmos-Framework repository (external site: github.com)
- Paper: Cosmos 3 technical report (external site: research.nvidia.com)
On AI on Hugging Face: Wan-AI/Wan2.2-TI2V-5B, nvidia/Cosmos3-Nano
Availability and license
Overall availability
Weights are downloadable from Hugging Face without an access gate under OpenMDW-1.1; the card states the model is ready for commercial and non-commercial use and lists global deployment geography.21
Availability is separate from permission: read the license before using or redistributing.
OpenMDW License Agreement, version 1.1 (OpenMDW-1.1) (external site: openmdw.ai)123
Plain-language guide to the OpenMDW License Agreement, version 1.1OpenMDW License Agreement, version 1.1 (Cosmos-Framework code) (external site: raw.githubusercontent.com)5
Plain-language guide to the OpenMDW License Agreement, version 1.1
OpenMDW-1.1 grants permission to deal in the model, its parameters, and related data, documentation, and software without restriction under copyright, patent, database, and trade secret rights. Distributors must keep a copy of the agreement and applicable notices, and rights end for anyone who sues claiming the materials infringe a patent or copyright, unless responding to a suit brought first. It places no restrictions on outputs. It is not on this catalog's OSI-approved list.34
Component reuse rights
- 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
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.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| WeightsCan the general public download the model parameters for this release? | Public | Weights are published on Hugging Face without an access gate.21 |
| Inference codeIs code for running the model published? | Public | The card documents inference with vLLM-Omni, vLLM (through a Cosmos-Framework plugin package), Hugging Face Diffusers, and SGLang Diffusion.16 |
| Training codeIs the code used to train the model published? | Partial | Cosmos-Framework publishes a distributed trainer whose documented recipes cover supervised fine-tuning (including a Nano vision SFT recipe). The report describes the internal training infrastructure used for both towers but does not identify it as Cosmos-Framework, and pre-training configurations were not found.679 |
| 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 summarizes the corpus (about 1.3B data points from 393 dataset entries, drawn from NVIDIA-owned data and public datasets, plus synthetic data) and links a public summary of training content. The report lists five synthetic datasets released on Hugging Face; most training data is not released.19 |
| Training recipeAre the training configuration and procedure documented in enough detail to follow? | Public | The technical report describes the training stages, data mixtures, optimizer settings, learning-rate schedules, and the token and GPU counts used for Nano.9 |
| Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only. | Partial | The card and report publish benchmark results, and the report releases one human evaluation benchmark (Cosmos-HUE); code to re-run all reported evaluations was not verified.19 |
What it is useful for
Run and use notes
- The card lists PyTorch, vLLM-Omni, Diffusers, and SGLang as runtimes; NVIDIA Ampere, Hopper, and Blackwell GPUs; and Linux as the tested operating system. It states that only BF16 precision is tested and gives a recommended vLLM-Omni serving command for an H200 GPU.1
Organization context
Provenance and derivatives
Trained by NVIDIA. The technical report states that Cosmos3-Nano adapts the Qwen3-VL 8B architecture and is initialized from pre-trained Qwen3-VL-8B weights (developed by the Qwen team at Alibaba Cloud), and that visual generation uses the video VAE encoder from Wan2.2-TI2V-5B (published on Hugging Face by Wan-AI). The card lists synthetic training data generated with HiDream-I1, Qwen-Image-2512, and Qwen3-VL.911211
- Derived from: Qwen3-VL-8B (external site: github.com) — Initialization weights for the language and vision backbone.
- Derived from: Wan2.2-TI2V-5B video VAE (external site: huggingface.co) — Video VAE encoder used for visual generation; published by Wan-AI under Apache 2.0.
Other releases in the NVIDIA Cosmos family
- NVIDIA Cosmos3-SuperModel-disclosure tier (USASI rubric v0.2): Open-weight
In the news
NVIDIA releases Cosmos3-H-Embodied-Nano and Cosmos3-H-Dreams surgical robotics world models
NVIDIA published two surgical robotics models on Hugging Face whose model cards give a release date of October 20, 2026, both under the NVIDIA Open Model License Agreement. The Cosmos3-H-Embodied-Nano card describes Cosmos3-Nano post-trained on the Open-H-Embodiment surgical robotics data jointly for forward dynamics, inverse dynamics and policy, so one checkpoint can predict robot actions and endoscopic video. The Cosmos3-H-Dreams card describes a real-time, action-conditioned surgical world model for the CMR Surgical Versius system, built on Cosmos3-H-Embodied-Nano and distilled into a few-step autoregressive student that generates endoscopic video from a camera frame and robot commands. Both cards say the Cosmos3-Nano architecture they inherit includes a Qwen3-VL-8B reasoning tower, and the cards describe intended uses in simulation, policy evaluation and synthetic data generation before use on a physical system. USASI has not tested these models.
What this catalog does not know
- Training-data information: unknown.
- Training-data access: unknown.
- Complete training pipeline: unknown.
Have a primary source? How to report a correction.
U.S. eligibility
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. The model is initialized from third-party Qwen3-VL weights, recorded under provenance; that base is not U.S.-developed.113912
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.
Share or cite this page
- X (opens X)
- Bluesky (opens Bluesky)
- LinkedIn (opens LinkedIn)
- Reddit (opens Reddit)
- Hacker News (opens Hacker News)
- Email (opens your email app)
- RSS updates
Cite this page
APA style
USASI. (2026, September 29). NVIDIA Cosmos3-Nano. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/cosmos3-nano/
BibTeX
@misc{usasi_cosmos3_nano,
author = {{USASI}},
title = {NVIDIA Cosmos3-Nano},
year = {2026},
month = sep,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/cosmos3-nano/}},
note = {United States of America Superintelligence. Last updated 2026-09-29}
}The date is when this page was last updated. Add the date you read it if your style needs one.
For maintainers: a “Listed in USASI” badge
Links to this page. It says the entry is listed, not endorsed or rated. About the badge
Markdown (for a README)
[](https://unitedstatesofamericasuperintelligence.com/open/cosmos3-nano/)
HTML
<a href="https://unitedstatesofamericasuperintelligence.com/open/cosmos3-nano/"><img src="https://unitedstatesofamericasuperintelligence.com/badges/listed.svg" alt="Listed in the USASI catalog" height="20"></a>