--- title: "Auto-PyTorch vs flower" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automl-auto-pytorch-vs-flwrlabs-flower" tools: ["automl-auto-pytorch", "flwrlabs-flower"] --- # Auto-PyTorch vs flower *GraphCanon updated Aug 4, 2026* ## Verdict Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick flower if a customizable, extendable federated learning framework supporting multiple ML frameworks, coded in Python. [Auto-PyTorch](https://github.com/automl/Auto-PyTorch) reports 2.5k GitHub stars, 303 forks, and 75 open issues, last pushed Apr 9, 2024. [flower](https://flower.ai) has 7.1k stars, 1.2k forks, and 368 open issues, last pushed Aug 4, 2026. Figures are from public GitHub metadata via [Auto-PyTorch's repository](https://github.com/automl/Auto-PyTorch) and [flower's repository](https://github.com/flwrlabs/flower). | | [Auto-PyTorch](/tools/automl-auto-pytorch.md) | [flower](/tools/flwrlabs-flower.md) | | --- | --- | --- | | Tagline | Automatic architecture search and hyperparameter optimization for PyTorch | A Friendly Federated AI Framework | | Stars | 2,541 | 7,067 | | Forks | 303 | 1,214 | | Open issues | 75 | 368 | | Language | Python | Python | | Adopt for | Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch. | A customizable, extendable federated learning framework supporting multiple ML frameworks, coded in Python. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Data & Retrieval, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Auto-PyTorch](/tools/automl-auto-pytorch.md) | [flower](/tools/flwrlabs-flower.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 846d | 0d | | Open issues (now) | 75 | 368 | | Full report | [trust report](/tools/automl-auto-pytorch/trust.md) | [trust report](/tools/flwrlabs-flower/trust.md) | ## Decision facts: Auto-PyTorch - **Adopt for:** Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch. ## Decision facts: flower - **Adopt for:** A customizable, extendable federated learning framework supporting multiple ML frameworks, coded in Python. ## Choose when ### Choose Auto-PyTorch if… - Tags unique to Auto-PyTorch: automl, deep-learning, tabular-data, time-series-forecasting. - Also covers Data & Retrieval. - Auto-PyTorch ships Docker support for self-hosted deployment. - Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models. ### Choose flower if… - Tags unique to flower: ai-frameworks, federated-learning, python, tensorflow. - When you require support for a wide range of machine learning frameworks including PyTorch, TensorFlow, and scikit-learn to integrate federated learning - More GitHub stars (7.1k vs 2.5k) - visibility, not fit. ## When NOT to use Auto-PyTorch - Avoid using it if your AI development focuses on frameworks other than PyTorch. - Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning. ## When NOT to use flower - Avoid if your use case demands real-time model updates or integration with specific ML frameworks not covered by Flower's framework support - Not recommended for projects where the federated learning setup requires extensive customization beyond what the extendable components offer ## Common questions ### What is the difference between Auto-PyTorch and flower? Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. flower: A Friendly Federated AI Framework. See the comparison table for live GitHub stats and shared categories. ### When should I choose Auto-PyTorch over flower? Choose Auto-PyTorch over flower when Tags unique to Auto-PyTorch: automl, deep-learning, tabular-data, time-series-forecasting; Also covers Data & Retrieval; Auto-PyTorch ships Docker support for self-hosted deployment; Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models. ### When should I choose flower over Auto-PyTorch? Choose flower over Auto-PyTorch when Tags unique to flower: ai-frameworks, federated-learning, python, tensorflow; When you require support for a wide range of machine learning frameworks including PyTorch, TensorFlow, and scikit-learn to integrate federated learning; More GitHub stars (7.1k vs 2.5k) - visibility, not fit. ### When should I avoid Auto-PyTorch? Avoid using it if your AI development focuses on frameworks other than PyTorch. Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning. ### When should I avoid flower? Avoid if your use case demands real-time model updates or integration with specific ML frameworks not covered by Flower's framework support Not recommended for projects where the federated learning setup requires extensive customization beyond what the extendable components offer ### Is Auto-PyTorch or flower more popular on GitHub? flower has more GitHub stars (7,067 vs 2,541). Stars measure visibility, not whether either tool fits your constraints. ### Are Auto-PyTorch and flower open source? Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, flower: Apache-2.0). ### Where can I find alternatives to Auto-PyTorch or flower? GraphCanon lists graph-backed alternatives at [Auto-PyTorch alternatives](/tools/automl-auto-pytorch/alternatives) and [flower alternatives](/tools/flwrlabs-flower/alternatives) ([Auto-PyTorch markdown twin](/tools/automl-auto-pytorch/alternatives.md), [flower markdown twin](/tools/flwrlabs-flower/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/automl-auto-pytorch-vs-flwrlabs-flower.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Auto-PyTorch or flower? Auto-PyTorch: Dormant. flower: Very 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 Auto-PyTorch and flower? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Auto-PyTorch trust report](/tools/automl-auto-pytorch/trust); [flower trust report](/tools/flwrlabs-flower/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automl-auto-pytorch`](/api/graphcanon/graph?tool=automl-auto-pytorch) - 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/_