--- title: "Curator vs FastDatasets" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-nemo-curator-vs-zhulinsen-fastdatasets" tools: ["nvidia-nemo-curator", "zhulinsen-fastdatasets"] --- # Curator vs FastDatasets *GraphCanon updated Aug 24, 2026* ## Verdict Pick Curator if scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks; pick FastDatasets if fastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. [Curator](https://github.com/NVIDIA-NeMo/Curator) reports 1.7k GitHub stars, 320 forks, and 280 open issues, last pushed Aug 21, 2026. [FastDatasets](https://github.com/ZhuLinsen/FastDatasets) has 222 stars, 43 forks, and 0 open issues, last pushed Aug 31, 2025. Figures are from public GitHub metadata via [Curator's repository](https://github.com/NVIDIA-NeMo/Curator) and [FastDatasets's repository](https://github.com/ZhuLinsen/FastDatasets). | | [Curator](/tools/nvidia-nemo-curator.md) | [FastDatasets](/tools/zhulinsen-fastdatasets.md) | | --- | --- | --- | | Tagline | Scalable data pre-processing and curation toolkit for LLMs | A powerful tool for creating high-quality training datasets for Large Language Models (LLMs) | | Stars | 1,731 | 222 | | Forks | 320 | 43 | | Open issues | 280 | 0 | | Language | Python | Python | | Adopt for | Scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks. | FastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Curator](/tools/nvidia-nemo-curator.md) | [FastDatasets](/tools/zhulinsen-fastdatasets.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 2d | 340d | | Open issues (now) | 280 | 0 | | Stars delta | +50 (30d) | Unknown | | Open issues delta | +8 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/nvidia-nemo-curator/trust.md) | [trust report](/tools/zhulinsen-fastdatasets/trust.md) | ## Shared compatibility - **Python**: [Curator](/tools/nvidia-nemo-curator.md) - Python runtime; [FastDatasets](/tools/zhulinsen-fastdatasets.md) - Python runtime ## Decision facts: Curator - **Adopt for:** Scalable toolkit for data pre-processing tailored to LLMs, featuring deduplication and quality checks. ## Decision facts: FastDatasets - **Adopt for:** FastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. ## Choose when ### Choose Curator if… - Tags unique to Curator: curation toolkit, data pre-processing, deduplication, llms. - You're working with NVIDIA NeMo models and require seamless integration. - More GitHub stars (1.7k vs 222) - visibility, not fit. ### Choose FastDatasets if… - Tags unique to FastDatasets: asyncio, dataset-generation, datasets, llm. - - When you need to generate datasets specifically tailored to improve the performance of LLMs. - Leaner open-issue backlog (0). ## When NOT to use Curator - Your dataset doesn't align with NVIDIA hardware specifications. - You prefer data curation tools that do not emphasize semantic processing. ## When NOT to use FastDatasets - - Avoid using if the project does not involve training or fine-tuning LLMs as its primary objective. - - If customization and flexibility are critical and your team prefers managing datasets manually for full control over each dataset creation process. ## Common questions ### What is the difference between Curator and FastDatasets? Curator: Scalable data pre-processing and curation toolkit for LLMs. FastDatasets: A powerful tool for creating high-quality training datasets for Large Language Models (LLMs). See the comparison table for live GitHub stats and shared categories. ### When should I choose Curator over FastDatasets? Choose Curator over FastDatasets when Tags unique to Curator: curation toolkit, data pre-processing, deduplication, llms; You're working with NVIDIA NeMo models and require seamless integration; More GitHub stars (1.7k vs 222) - visibility, not fit. ### When should I choose FastDatasets over Curator? Choose FastDatasets over Curator when Tags unique to FastDatasets: asyncio, dataset-generation, datasets, llm; - When you need to generate datasets specifically tailored to improve the performance of LLMs; Leaner open-issue backlog (0). ### When should I avoid Curator? Your dataset doesn't align with NVIDIA hardware specifications. You prefer data curation tools that do not emphasize semantic processing. ### When should I avoid FastDatasets? - Avoid using if the project does not involve training or fine-tuning LLMs as its primary objective. - If customization and flexibility are critical and your team prefers managing datasets manually for full control over each dataset creation process. ### Is Curator or FastDatasets more popular on GitHub? Curator has more GitHub stars (1,731 vs 222). Stars measure visibility, not whether either tool fits your constraints. ### Are Curator and FastDatasets open source? Yes - both are open-source projects on GitHub (Curator: Apache-2.0, FastDatasets: Apache-2.0). ### Where can I find alternatives to Curator or FastDatasets? GraphCanon lists graph-backed alternatives at [Curator alternatives](/tools/nvidia-nemo-curator/alternatives) and [FastDatasets alternatives](/tools/zhulinsen-fastdatasets/alternatives) ([Curator markdown twin](/tools/nvidia-nemo-curator/alternatives.md), [FastDatasets markdown twin](/tools/zhulinsen-fastdatasets/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/nvidia-nemo-curator-vs-zhulinsen-fastdatasets.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Curator or FastDatasets? Curator: Very active. FastDatasets: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for Curator and FastDatasets? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Curator trust report](/tools/nvidia-nemo-curator/trust); [FastDatasets trust report](/tools/zhulinsen-fastdatasets/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nvidia-nemo-curator`](/api/graphcanon/graph?tool=nvidia-nemo-curator) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_