NVIDIA Nemotron 3 Ultra 550B-A55B
NVIDIA Nemotron 3 Ultra 550B-A55B is an open-weight model release in the NVIDIA Nemotron family from NVIDIA1, version 3 Ultra (550B-A55B), v1.0, released Jun 4, 2026. Its weights can be downloaded by the public12 under the OpenMDW License Agreement, version 1.113.
Nemotron 3 Ultra is an NVIDIA language model with 550B total and 55B active parameters, built on a hybrid Mamba-2 and attention architecture with latent mixture-of-experts layers and multi-token prediction. Reasoning can be switched on or off through the chat template. NVIDIA released BF16 and NVFP4 checkpoints and a separate base checkpoint on Hugging Face.1
- Model hub: Model card (BF16) (external site: huggingface.co)
- License: OpenMDW License Agreement, version 1.1 (external site: raw.githubusercontent.com)
- Documentation: Nemotron 3 Ultra training recipe (external site: github.com)
On AI on Hugging Face: nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
Availability and license
Overall availability
Weights are downloadable from Hugging Face under the OpenMDW-1.1 license; the repository metadata showed no access gate when checked.12
Availability is separate from permission: read the license before using or redistributing.
OpenMDW License Agreement, version 1.1 (external site: raw.githubusercontent.com)13
Plain-language guide to the OpenMDW License Agreement, version 1.1Apache License 2.0 (Nemotron Developer Repository training recipes) (external site: raw.githubusercontent.com)5
Plain-language guide to the Apache License 2.0
OpenMDW-1.1 grants free permission to use, modify, and share the model materials without restriction, including under copyright, patent, database, and trade secret rights. Redistributors must include a copy of the agreement and keep applicable origin notices. All rights end for anyone who sues claiming the materials infringe a patent or copyright, unless responding to a suit brought against them first. It imposes no conditions on outputs, disclaims warranties, and leaves clearing third-party rights to the user. The SPDX list (version 3.29.0) includes OpenMDW-1.0 but not version 1.1, so no SPDX ID is recorded.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 | BF16 and NVFP4 post-trained checkpoints and a BF16 base checkpoint are published on Hugging Face.12 |
| Inference codeIs code for running the model published? | Public | The model card gives deployment instructions for vLLM, SGLang, and TensorRT-LLM.1 |
| Training codeIs the code used to train the model published? | Public | The Apache-2.0 Nemotron Developer Repository provides pretraining and SFT recipes built on Megatron-Bridge and a representative RL/distillation pass using NeMo RL.65 |
| 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. | Partial | The model card says NVIDIA releases its final pre-training and post-training data, with an ungated sample set and gating and approval required for the remaining code, math, and multilingual data. It also lists third-party and NVIDIA datasets used in training as private and not publicly accessible. NVIDIA's training recipe adds that the data for the 1M-token long-context phase is not open source.16 |
| 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 model card lists the pre- and post-training datasets. Major portions are released in Hugging Face collections, some requiring access approval, while several third-party and NVIDIA datasets are listed as private and not publicly accessible.17 |
| Training recipeAre the training configuration and procedure documented in enough detail to follow? | Partial | NVIDIA's recipe covers pretraining and SFT, but states that the full multi-iteration RL and on-policy distillation pipeline is not reproduced because the intermediate teacher checkpoints it depends on have not been released. It also omits the 1M-token long-context pretraining phase because that data is not open-source.6 |
| Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only. | Public | The model card publishes benchmark results and points to the NeMo Evaluator SDK for replication; it says some benchmarks used internal scaffolding not yet open-sourced.1 |
What it is useful for
The model card lists agentic workflows, long-context analysis, tool use, multilingual reasoning, and retrieval-augmented generation, and states the model is ready for commercial and non-commercial use.1
Run and use notes
- The model card documents serving with vLLM, SGLang, and TensorRT-LLM, and lists NVIDIA Hopper (H100, H200), Grace Blackwell (GB200, GB300), and Blackwell (B200, B300) GPUs as test hardware.1
- For the BF16 checkpoint, the model card states a minimum of 8x GB200/B200/GB300/B300, 16x H100, or 8x H200 GPUs, and points to the separate NVFP4 checkpoint for a smaller footprint.1
Organization context
Provenance and derivatives
Post-trained by NVIDIA (supervised fine-tuning, reinforcement learning, and multi-domain on-policy distillation) from its own pre-trained Nemotron 3 Ultra base checkpoint. The model card says post-training synthetic data was generated with teacher models, including third-party open models such as GPT-OSS-120B.1
- Derived from: NVIDIA-Nemotron-3-Ultra-550B-A55B-Base-BF16 (external site: huggingface.co) — NVIDIA's pre-trained base checkpoint for this release.
Other releases in the NVIDIA Nemotron family
- NVIDIA Nemotron 3 Super 120B-A12BModel-disclosure tier (USASI rubric v0.2): Open-weight
- NVIDIA Nemotron 3.5 Lightning 30B-A3BModel-disclosure tier (USASI rubric v0.2): Open-weight
- NVIDIA Nemotron 3.5 Super VL 120B-A12BModel-disclosure tier (USASI rubric v0.2): Open-weight
- NVIDIA Nemotron Labs Dory1.0-4BModel-disclosure tier (USASI rubric v0.2): Open-weight
What this catalog does not know
- Training-data information: unknown.
- Complete training pipeline: unknown.
Have a primary source? How to report a correction.
U.S. eligibility
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.
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APA style
USASI. (2026, October 2). NVIDIA Nemotron 3 Ultra 550B-A55B. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/nemotron-3-ultra-550b-a55b/
BibTeX
@misc{usasi_nemotron_3_ultra_550b_a55b,
author = {{USASI}},
title = {NVIDIA Nemotron 3 Ultra 550B-A55B},
year = {2026},
month = oct,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/nemotron-3-ultra-550b-a55b/}},
note = {United States of America Superintelligence. Last updated 2026-10-02}
}The date is when this page was last updated. Add the date you read it if your style needs one.
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