--- title: "lightly-train vs onepanel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightly-ai-lightly-train-vs-onepanelio-onepanel" tools: ["lightly-ai-lightly-train", "onepanelio-onepanel"] --- # lightly-train vs onepanel *GraphCanon updated Aug 22, 2026* ## Verdict 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; pick onepanel if onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the. [lightly-train](https://docs.lightly.ai/train) reports 1.6k GitHub stars, 107 forks, and 68 open issues, last pushed Aug 14, 2026. [onepanel](https://docs.onepanel.ai/) has 730 stars, 73 forks, and 102 open issues, last pushed Feb 25, 2023. Figures are from public GitHub metadata via [lightly-train's repository](https://github.com/lightly-ai/lightly-train) and [onepanel's repository](https://github.com/onepanelio/onepanel). | | [lightly-train](/tools/lightly-ai-lightly-train.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Tagline | All-in-one training for vision models: pretraining, fine-tuning, distillation. | The open source, end-to-end computer vision platform. | | Stars | 1,650 | 730 | | Forks | 107 | 73 | | Open issues | 68 | 102 | | Language | Python | Go | | 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. | Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | Computer Vision, Model Training | Computer Vision, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lightly-train](/tools/lightly-ai-lightly-train.md) | [onepanel](/tools/onepanelio-onepanel.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 7d | 1252d | | Open issues (now) | 68 | 102 | | Stars delta | +28 (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Full report | [trust report](/tools/lightly-ai-lightly-train/trust.md) | [trust report](/tools/onepanelio-onepanel/trust.md) | ## 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. ## Decision facts: onepanel - **Adopt for:** Onepanel is an open source tool designed for computer vision projects with capabilities spanning from data labeling to model tuning and deployment, all supported by a Go-based codebase under the Apache-2.0 license. ## Choose when ### Choose lightly-train if… - lightly-train is primarily Python; onepanel is Go. - License: lightly-train is AGPL-3.0, onepanel is Apache-2.0. - Requirements: Min 8 GB RAM. - Tags unique to lightly-train: computer-vision, contrastive-learning, deep-learning, depth-estimation. - 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 onepanel if… - onepanel is primarily Go; lightly-train is Python. - License: onepanel is Apache-2.0, lightly-train is AGPL-3.0. - Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning. - Also covers Inference & Serving. - onepanel ships Docker support for self-hosted deployment. - When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ## When NOT to use lightly-train - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use onepanel - Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. - Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ## Common questions ### What is the difference between lightly-train and onepanel? lightly-train: All-in-one training for vision models: pretraining, fine-tuning, distillation.. onepanel: The open source, end-to-end computer vision platform.. See the comparison table for live GitHub stats and shared categories. ### When should I choose lightly-train over onepanel? Choose lightly-train over onepanel when lightly-train is primarily Python; onepanel is Go; License: lightly-train is AGPL-3.0, onepanel is Apache-2.0; Requirements: Min 8 GB RAM; Tags unique to lightly-train: computer-vision, contrastive-learning, deep-learning, depth-estimation; 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 choose onepanel over lightly-train? Choose onepanel over lightly-train when onepanel is primarily Go; lightly-train is Python; License: onepanel is Apache-2.0, lightly-train is AGPL-3.0; Tags unique to onepanel: aiops, annotation, deeplearning, hyperparameter-tuning; Also covers Inference & Serving; onepanel ships Docker support for self-hosted deployment; When you need an end-to-end platform that supports multiple aspects of computer vision including advanced functionalities such as hyperparameter tuning and automated workflows. ### When should I avoid lightly-train? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid onepanel? Avoid using Onepanel for projects that require extensive Java-based development because it is written in Go. Not suitable if you seek a platform focusing solely on model serving or inference without capabilities to go back upstream into data labeling and preprocessing stages. ### Is lightly-train or onepanel more popular on GitHub? lightly-train has more GitHub stars (1,650 vs 730). Stars measure visibility, not whether either tool fits your constraints. ### Are lightly-train and onepanel open source? Yes - both are open-source projects on GitHub (lightly-train: AGPL-3.0, onepanel: Apache-2.0). ### Where can I find alternatives to lightly-train or onepanel? GraphCanon lists graph-backed alternatives at [lightly-train alternatives](/tools/lightly-ai-lightly-train/alternatives) and [onepanel alternatives](/tools/onepanelio-onepanel/alternatives) ([lightly-train markdown twin](/tools/lightly-ai-lightly-train/alternatives.md), [onepanel markdown twin](/tools/onepanelio-onepanel/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-train-vs-onepanelio-onepanel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lightly-train or onepanel? lightly-train: Active. onepanel: Dormant. 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-train and onepanel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lightly-train trust report](/tools/lightly-ai-lightly-train/trust); [onepanel trust report](/tools/onepanelio-onepanel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightly-ai-lightly-train`](/api/graphcanon/graph?tool=lightly-ai-lightly-train) - 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/_