NeMo Curator
NVIDIAGPU-accelerated toolkit for curating LLM training data across text, image, video, and audio: extraction, language ID, exact/fuzzy/substring deduplication, quality classification, and synthetic data generation. NVIDIA uses it for the Nemotron-4 pretraining data (8+ trillion tokens of multilingual web data) and the Nemotron-CC curation pipeline.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public(NVIDIA/NeMo-Curator)
- core features withheld
- no
Fully OSI-licensed (Apache-2.0), full source public. Vendor-backed but not gated.
- https://github.com/NVIDIA/NeMo-Curator/blob/main/LICENSE recorded 2026-08-13
Apache License Version 2.0 text
- https://raw.githubusercontent.com/NVIDIA-NeMo/Curator/main/LICENSE recorded 2026-09-29
LICENSE is the Apache License text: "Apache License" and "APPENDIX: How to apply the Apache License to your work."
- https://raw.githubusercontent.com/NVIDIA-NeMo/Curator/main/pyproject.toml recorded 2026-09-29
pyproject.toml declares "License :: OSI Approved :: Apache Software License". Searched the body for enterprise, license key, non-commercial and proprietary: none.
- https://raw.githubusercontent.com/NVIDIA-NeMo/Curator/main/README.md recorded 2026-09-29
README states "NeMo Curator is released under the **Apache License 2.0**" and documents install from the published repo. Searched the body for enterprise, paid tier, license key, proprietary and non-commercial: none.
Adoption
1 high confidencePyPI downloads for the declared nemo-curator package are the usage signal recorded for this tool.
- https://pypistats.org/api/packages/nemo-curator/recent recorded 2026-08-13
4,075 downloads in the trailing 30 days for nemo-curator
Capability
5 high confidenceNeMo Curator is judged through Nemotron-CC, the corpus built with it, since the toolkit has no benchmark of its own. The Nemotron-CC paper reports its high-quality subset improving MMLU over DCLM, which puts the toolkit level with DCLM.
- https://arxiv.org/abs/2412.02595 recorded 2026-09-29
Nemotron-CC abstract: "a high-quality subset of our data improves MMLU by 5.6 over DCLM" and its full dataset has "four times more unique real tokens than DCLM".
Verified 2026-09-24