Home/Compare/Auto-PyTorch vs flower

Comparison

Auto-PyTorch vs flower

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.

Markdown twin · Auto-PyTorch alternatives · flower alternatives

GraphCanon updated 2w

Auto-PyTorch logo

Auto-PyTorch

automl/Auto-PyTorch

2.5kpushed Apr 9, 2024
vs
flower logo

flower

flwrlabs/flower

7.1kpushed Aug 4, 2026

Trust & integrity

SignalAuto-PyTorchflower
Maintenance
Dormant (846d since push)
As of 2w · github_public_v1
Very active (0d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

Auto-PyTorch
Automatic architecture search and hyperparameter optimization for PyTorch
flower
A Friendly Federated AI Framework

Stars

Auto-PyTorch
2.5k
flower
7.1k

Forks

Auto-PyTorch
303
flower
1.2k

Open issues

Auto-PyTorch
75
flower
368

Language

Auto-PyTorch
Python
flower
Python

Adopt for

Auto-PyTorch
Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch.
flower
A customizable, extendable federated learning framework supporting multiple ML frameworks, coded in Python.

Persona

Auto-PyTorch
-
flower
-

Runtime

Auto-PyTorch
-
flower
-

License

Auto-PyTorch
Apache-2.0
flower
Apache-2.0

Last pushed

Auto-PyTorch
Apr 9, 2024
flower
Aug 4, 2026

Categories

Auto-PyTorch
Data & Retrieval, Model Training
flower
Model Training

Trust and health

Maintenance

Auto-PyTorch
Dormant (18%)
flower
Very active (96%)

Days since push

Auto-PyTorch
846d
flower
0d

Open issues (now)

Auto-PyTorch
75
flower
368

OSV dependency advisories

Auto-PyTorch
Published findings
flower
No lockfile (source not queried)

Full report

Auto-PyTorch
Trust report

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.

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.

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 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

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: Auto-PyTorch 2.5k · flower 7.1k (synced Aug 4, 2026).

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 and flower alternatives (Auto-PyTorch markdown twin, flower markdown twin), 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 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; flower trust report.

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