Comparison
autokeras vs hub
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 hub if hub is specifically tailored to Python developers who wish to incorporate transfer learning into their TensorFlow projects with pre-trained model components for applications such as image classification.
Markdown twin · autokeras alternatives · hub alternatives
GraphCanon updated 2d
Trust & integrity
| Signal | autokeras | hub |
|---|---|---|
| Maintenance | Slowing (251d since push) As of 3w · github_public_v1 | Dormant (581d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 2d · 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
- hub
- A library for transfer learning by reusing parts of TensorFlow models.
Stars
- autokeras
- 9.3k
- hub
- 3.5k
Forks
- autokeras
- 1.4k
- hub
- 1.6k
Open issues
- autokeras
- 161
- hub
- 6
Language
- autokeras
- Python
- hub
- 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+.
- hub
- hub is specifically tailored to Python developers who wish to incorporate transfer learning into their TensorFlow projects with pre-trained model components for applications such as image classification.
Persona
- autokeras
- -
- hub
- -
Runtime
- autokeras
- -
- hub
- -
License
- autokeras
- Apache-2.0
- hub
- hub is licensed under Apache-2.0, allowing for broad use in both open source and commercial projects.
Last pushed
- autokeras
- Nov 25, 2025
- hub
- Jan 17, 2025
Categories
- autokeras
- Developer Tools, Model Training
- hub
- Data & Retrieval, Model Training
Trust and health
Maintenance
- autokeras
- Slowing (36%)
- hub
- Dormant (18%)
Days since push
- autokeras
- 251d
- hub
- 581d
Open issues (now)
- autokeras
- 161
- hub
- 6
Stars delta
- autokeras
- Unknown
- hub
- +1 (30d)
Open issues delta
- autokeras
- Unknown
- hub
- -5 (30d)
Full report
- autokeras
- Trust report
- hub
- Trust report
Choose autokeras if…
- 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 hub if…
- Pricing: The core functionalities of hub are free to use with an open-source license; however, additional services or enterprise support might incur costs..
- Requirements: Requires a Python environment and TensorFlow installation to operate..
- Tags unique to hub: embeddings, image-classification, ml, python.
- Also covers Data & Retrieval.
- When you need to leverage existing TensorFlow models and integrate specific parts of them for tasks like embedding or image-classification without retraining the entire model from scratch.
When NOT to use hub
- When working strictly with non-TensorFlow frameworks such as PyTorch or MXNet, as hub is built specifically for enhancing and reusing models within TensorFlow.
- If your project requires a more generalized approach to machine-learning without reliance on pre-existing model components, focusing instead on training models from the ground up.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (keras-team/autokeras) · observed Aug 4, 2026
- GitHub forks (keras-team/autokeras) · observed Aug 4, 2026
- Last push (keras-team/autokeras) · observed Nov 25, 2025
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tensorflow/hub) · observed Aug 22, 2026
- GitHub forks (tensorflow/hub) · observed Aug 22, 2026
- Last push (tensorflow/hub) · observed Jan 17, 2025
- License file (Apache-2.0) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: autokeras 9.3k · hub 3.5k (synced Aug 4, 2026).
Common questions
- What is the difference between autokeras and hub?
- autokeras: AutoML library for deep learning. hub: A library for transfer learning by reusing parts of TensorFlow models.. See the comparison table for live GitHub stats and shared categories.
- When should I choose autokeras over hub?
- Choose autokeras over hub when 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 hub over autokeras?
- Choose hub over autokeras when Pricing: The core functionalities of hub are free to use with an open-source license; however, additional services or enterprise support might incur costs.; Requirements: Requires a Python environment and TensorFlow installation to operate.; Tags unique to hub: embeddings, image-classification, ml, python; Also covers Data & Retrieval; When you need to leverage existing TensorFlow models and integrate specific parts of them for tasks like embedding or image-classification without retraining the entire model from scratch.
- 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 hub?
- When working strictly with non-TensorFlow frameworks such as PyTorch or MXNet, as hub is built specifically for enhancing and reusing models within TensorFlow. If your project requires a more generalized approach to machine-learning without reliance on pre-existing model components, focusing instead on training models from the ground up.
- Is autokeras or hub more popular on GitHub?
- autokeras has more GitHub stars (9,328 vs 3,523). Stars measure visibility, not whether either tool fits your constraints.
- Are autokeras and hub open source?
- Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, hub: Apache-2.0).
- Where can I find alternatives to autokeras or hub?
- GraphCanon lists graph-backed alternatives at autokeras alternatives and hub alternatives (autokeras markdown twin, hub 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 hub?
- autokeras: Slowing. hub: 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 autokeras and hub?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autokeras trust report; hub trust report.