--- title: "lightly vs lightly-train" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightly-ai-lightly-vs-lightly-ai-lightly-train" tools: ["lightly-ai-lightly", "lightly-ai-lightly-train"] --- # lightly vs lightly-train *GraphCanon updated Aug 22, 2026* ## Verdict Pick lightly if lightly specializes in self-supervised learning for image data to improve computer vision models without labeled datasets; pick lightly-train if lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. [lightly](https://docs.lightly.ai/self-supervised-learning/) reports 3.8k GitHub stars, 354 forks, and 97 open issues, last pushed Aug 21, 2026. [lightly-train](https://docs.lightly.ai/train) has 1.6k stars, 107 forks, and 68 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [lightly's repository](https://github.com/lightly-ai/lightly) and [lightly-train's repository](https://github.com/lightly-ai/lightly-train). | | [lightly](/tools/lightly-ai-lightly.md) | [lightly-train](/tools/lightly-ai-lightly-train.md) | | --- | --- | --- | | Tagline | A python library for self-supervised learning on images. | All-in-one training for vision models: pretraining, fine-tuning, distillation. | | Stars | 3,795 | 1,650 | | Forks | 354 | 107 | | Open issues | 97 | 68 | | Language | Python | Python | | Adopt for | Lightly specializes in self-supervised learning for image data to improve computer vision models without labeled datasets. | Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. | | Persona | - | - | | Runtime | - | - | | License | MIT | AGPL-3.0 | | Categories | Computer Vision, Model Training | Computer Vision, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lightly](/tools/lightly-ai-lightly.md) | [lightly-train](/tools/lightly-ai-lightly-train.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 7d | | Open issues (now) | 97 | 68 | | Stars delta | +11 (30d) | +28 (30d) | | Open issues delta | +4 (30d) | +5 (30d) | | Full report | [trust report](/tools/lightly-ai-lightly/trust.md) | [trust report](/tools/lightly-ai-lightly-train/trust.md) | ## Shared compatibility - **Python**: [lightly](/tools/lightly-ai-lightly.md) - Python runtime; [lightly-train](/tools/lightly-ai-lightly-train.md) - Python runtime ## Decision facts: lightly - **Adopt for:** Lightly specializes in self-supervised learning for image data to improve computer vision models without labeled datasets. ## Decision facts: lightly-train - **Requirements:** Min 8 GB RAM - **Adopt for:** Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ## Choose when ### Choose lightly if… - License: lightly is MIT, lightly-train is AGPL-3.0. - Tags unique to lightly: self-supervised-learning. - You need to enhance model performance with unlabeled image data. ### Choose lightly-train if… - License: lightly-train is AGPL-3.0, lightly is MIT. - Requirements: Min 8 GB RAM. - Tags unique to lightly-train: depth-estimation, dinov2, dinov3, distillation. - Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ## When NOT to use lightly - Labeled datasets are abundant and of high quality for your use case. - Project requirements strictly limit the use of Python-based libraries. ## When NOT to use lightly-train - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## Common questions ### What is the difference between lightly and lightly-train? lightly: A python library for self-supervised learning on images.. lightly-train: All-in-one training for vision models: pretraining, fine-tuning, distillation.. See the comparison table for live GitHub stats and shared categories. ### When should I choose lightly over lightly-train? Choose lightly over lightly-train when License: lightly is MIT, lightly-train is AGPL-3.0; Tags unique to lightly: self-supervised-learning; You need to enhance model performance with unlabeled image data. ### When should I choose lightly-train over lightly? Choose lightly-train over lightly when License: lightly-train is AGPL-3.0, lightly is MIT; Requirements: Min 8 GB RAM; Tags unique to lightly-train: depth-estimation, dinov2, dinov3, distillation; Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation. ### When should I avoid lightly? Labeled datasets are abundant and of high quality for your use case. Project requirements strictly limit the use of Python-based libraries. ### When should I avoid lightly-train? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is lightly or lightly-train more popular on GitHub? lightly has more GitHub stars (3,795 vs 1,650). Stars measure visibility, not whether either tool fits your constraints. ### Are lightly and lightly-train open source? Yes - both are open-source projects on GitHub (lightly: MIT, lightly-train: AGPL-3.0). ### Where can I find alternatives to lightly or lightly-train? GraphCanon lists graph-backed alternatives at [lightly alternatives](/tools/lightly-ai-lightly/alternatives) and [lightly-train alternatives](/tools/lightly-ai-lightly-train/alternatives) ([lightly markdown twin](/tools/lightly-ai-lightly/alternatives.md), [lightly-train markdown twin](/tools/lightly-ai-lightly-train/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/lightly-ai-lightly-vs-lightly-ai-lightly-train.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lightly or lightly-train? lightly: Very active. lightly-train: Active. 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 lightly and lightly-train? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lightly trust report](/tools/lightly-ai-lightly/trust); [lightly-train trust report](/tools/lightly-ai-lightly-train/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightly-ai-lightly`](/api/graphcanon/graph?tool=lightly-ai-lightly) - 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/_