Comparison
penzai vs autokeras
Verdict
Pick penzai if penzai supports fine-tuning and interpretability features in neural network research through JAX; 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+.
Markdown twin · penzai alternatives · autokeras alternatives
GraphCanon updated Sep 30, 2026
9views this month
vs
Trust & integrity
| Signal | penzai | autokeras |
|---|---|---|
| Maintenance | Archived (454d since push) As of Sep 19, 2026 · github_public_v1 | Slowing (309d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 19, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- penzai
- A JAX research toolkit for building, editing, and visualizing neural networks.
- autokeras
- AutoML library for deep learning
Stars
- penzai
- 1.9k
- autokeras
- 9.3k
Forks
- penzai
- 69
- autokeras
- 1.4k
Open issues
- penzai
- 21
- autokeras
- 161
Language
- penzai
- Python
- autokeras
- Python
Adopt for
- penzai
- Penzai supports fine-tuning and interpretability features in neural network research through JAX.
- autokeras
- AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+.
Persona
- penzai
- -
- autokeras
- -
Runtime
- penzai
- -
- autokeras
- -
License
- penzai
- Penzai operates under an Apache-2.0 license, offering permissive rights for software use, modification, and distribution.
- autokeras
- Apache-2.0
Last pushed
- penzai
- Jun 22, 2025
- autokeras
- Nov 25, 2025
Categories
- penzai
- Model Training
- autokeras
- Developer Tools, Model Training
Trust and health
Maintenance
- penzai
- Archived (8%)
- autokeras
- Slowing (36%)
Days since push
- penzai
- 454d
- autokeras
- 309d
Archived on GitHub
- penzai
- Yes
- autokeras
- No
Open issues (now)
- penzai
- 21
- autokeras
- 161
Stars delta
- penzai
- +8 (30d)
- autokeras
- +7 (30d)
Open issues delta
- penzai
- +4 (30d)
- autokeras
- 0 (30d)
Full report
- penzai
- Trust report
- autokeras
- Trust report
Shared compatibility
- Python · penzai: Python runtime · autokeras: Python runtime
Choose penzai if…
- Requirements: Ensure compatibility with Python and JAX libraries as they are crucial for leveraging Penzai's toolkit..
- Tags unique to penzai: fine-tuning, interpretability, jax, neural-networks.
- When your AI development tasks require detailed visualization capabilities for neural networks, as Penzai integrates advanced visual components tailored to these needs.
When NOT to use penzai
- Avoid if you are strictly working with frameworks that do not support or are incompatible with JAX, as Penzai is specifically designed for use within the JAX ecosystem.
- Do not choose Penzai if your project requires a focus on backend model deployment rather than research-oriented functionalities like visualization and interpretability.
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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (google-deepmind/penzai) · observed Sep 20, 2026
- GitHub forks (google-deepmind/penzai) · observed Sep 20, 2026
- Last push (google-deepmind/penzai) · observed Jun 22, 2025
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (keras-team/autokeras) · observed Sep 30, 2026
- GitHub forks (keras-team/autokeras) · observed Sep 30, 2026
- Last push (keras-team/autokeras) · observed Nov 25, 2025
- License file (Apache-2.0) · observed Sep 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: penzai 1.9k · autokeras 9.3k (synced Sep 20, 2026).
Common questions
- What is the difference between penzai and autokeras?
- penzai: A JAX research toolkit for building, editing, and visualizing neural networks.. autokeras: AutoML library for deep learning. See the comparison table for live GitHub stats and shared categories.
- When should I choose penzai over autokeras?
- Choose penzai over autokeras when Requirements: Ensure compatibility with Python and JAX libraries as they are crucial for leveraging Penzai's toolkit.; Tags unique to penzai: fine-tuning, interpretability, jax, neural-networks; When your AI development tasks require detailed visualization capabilities for neural networks, as Penzai integrates advanced visual components tailored to these needs.
- When should I choose autokeras over penzai?
- Choose autokeras over penzai 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 avoid penzai?
- Avoid if you are strictly working with frameworks that do not support or are incompatible with JAX, as Penzai is specifically designed for use within the JAX ecosystem. Do not choose Penzai if your project requires a focus on backend model deployment rather than research-oriented functionalities like visualization and interpretability.
- 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.
- Is penzai or autokeras more popular on GitHub?
- autokeras has more GitHub stars (9,335 vs 1,900). Stars measure visibility, not whether either tool fits your constraints.
- Are penzai and autokeras open source?
- Yes - both are open-source projects on GitHub (penzai: Apache-2.0, autokeras: Apache-2.0).
- Where can I find alternatives to penzai or autokeras?
- GraphCanon lists graph-backed alternatives at penzai alternatives and autokeras alternatives (penzai markdown twin, autokeras 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, penzai or autokeras?
- penzai: Archived. autokeras: Slowing. 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 penzai and autokeras?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: penzai trust report; autokeras trust report.