Home/Compare/autokeras vs optuna

Comparison

autokeras vs optuna

Verdict

Pick autokeras if autoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+; pick optuna if optuna automates hyperparameter tuning in Python, integrating seamlessly with major ML frameworks.

Markdown twin · autokeras alternatives · optuna alternatives

GraphCanon updated 3w

autokeras logo

autokeras

keras-team/autokeras

9.3kpushed Nov 25, 2025
vs
optuna logo

optuna

optuna/optuna

15kpushed Aug 3, 2026

Trust & integrity

Signalautokerasoptuna
Maintenance
Slowing (251d since push)
As of 3w · github_public_v1
Very active (1d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization account
As of 3w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
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

autokeras
AutoML library for deep learning
optuna
A hyperparameter optimization framework

Stars

autokeras
9.3k
optuna
15k

Forks

autokeras
1.4k
optuna
1.4k

Open issues

autokeras
161
optuna
16

Language

autokeras
Python
optuna
Python

Adopt for

autokeras
AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+.
optuna
Optuna automates hyperparameter tuning in Python, integrating seamlessly with major ML frameworks.

Persona

autokeras
-
optuna
-

Runtime

autokeras
-
optuna
-

License

autokeras
Apache-2.0
optuna
MIT

Last pushed

autokeras
Nov 25, 2025
optuna
Aug 3, 2026

Categories

autokeras
Developer Tools, Model Training
optuna
Model Training

Trust and health

Maintenance

autokeras
Slowing (36%)
optuna
Very active (96%)

Days since push

autokeras
251d
optuna
1d

Open issues (now)

autokeras
161
optuna
16

Full report

autokeras
Trust report

Shared compatibility

  • Python · autokeras: Python runtime · optuna: Python runtime

Choose autokeras if…

  • License: autokeras is Apache-2.0, optuna is MIT.
  • Tags unique to autokeras: autodl, automl, deep-learning, keras.
  • Also covers Developer Tools.
  • When your project involves deep learning tasks requiring minimal manual intervention in designing models.

When NOT to use autokeras

  • When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible.
  • If your project emphasizes transparent, understandable model architecture over automated generation without human oversight.

Choose optuna if…

  • License: optuna is MIT, autokeras is Apache-2.0.
  • Tags unique to optuna: distributed, hyperparameter-optimization, parallel, python.
  • When you need to streamline the hyperparameter tuning process for machine learning models built in Python.

When NOT to use optuna

  • If your project is not compatible with Python, as Optuna does not support other languages directly out of box.
  • Projects requiring manual control over every aspect of hyperparameter tuning might find Optuna too automated for their needs.

Explore

Sources

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

GitHub stars on cards: autokeras 9.3k · optuna 15k (synced Aug 4, 2026).

Common questions

What is the difference between autokeras and optuna?
autokeras: AutoML library for deep learning. optuna: A hyperparameter optimization framework. See the comparison table for live GitHub stats and shared categories.
When should I choose autokeras over optuna?
Choose autokeras over optuna when License: autokeras is Apache-2.0, optuna is MIT; Tags unique to autokeras: autodl, automl, deep-learning, keras; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models.
When should I choose optuna over autokeras?
Choose optuna over autokeras when License: optuna is MIT, autokeras is Apache-2.0; Tags unique to optuna: distributed, hyperparameter-optimization, parallel, python; When you need to streamline the hyperparameter tuning process for machine learning models built in Python.
When should I avoid autokeras?
When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible. If your project emphasizes transparent, understandable model architecture over automated generation without human oversight.
When should I avoid optuna?
If your project is not compatible with Python, as Optuna does not support other languages directly out of box. Projects requiring manual control over every aspect of hyperparameter tuning might find Optuna too automated for their needs.
Is autokeras or optuna more popular on GitHub?
optuna has more GitHub stars (14,603 vs 9,328). Stars measure visibility, not whether either tool fits your constraints.
Are autokeras and optuna open source?
Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, optuna: MIT).
Where can I find alternatives to autokeras or optuna?
GraphCanon lists graph-backed alternatives at autokeras alternatives and optuna alternatives (autokeras markdown twin, optuna 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, autokeras or optuna?
autokeras: Slowing. optuna: 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 autokeras and optuna?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autokeras trust report; optuna trust report.

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