Comparison
autokeras vs pytorch-meta
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 pytorch-meta if pyTorch-Meta focuses on facilitating few-shot learning and meta-learning with PyTorch, offering extensions and data-loaders specifically for these tasks.
Markdown twin · autokeras alternatives · pytorch-meta alternatives
GraphCanon updated Oct 3, 2026
12views this month
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Trust & integrity
| Signal | autokeras | pytorch-meta |
|---|---|---|
| Maintenance | Slowing (309d since push) As of Sep 30, 2026 · github_public_v1 | Dormant (1173d since push) As of Oct 3, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 | Not a fork · Personal account As of Oct 3, 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
- autokeras
- AutoML library for deep learning
- pytorch-meta
- Extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Stars
- autokeras
- 9.3k
- pytorch-meta
- 2.1k
Forks
- autokeras
- 1.4k
- pytorch-meta
- 264
Open issues
- autokeras
- 161
- pytorch-meta
- 61
Language
- autokeras
- Python
- pytorch-meta
- 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+.
- pytorch-meta
- PyTorch-Meta focuses on facilitating few-shot learning and meta-learning with PyTorch, offering extensions and data-loaders specifically for these tasks.
Persona
- autokeras
- -
- pytorch-meta
- -
Runtime
- autokeras
- -
- pytorch-meta
- -
License
- autokeras
- Apache-2.0
- pytorch-meta
- MIT
Last pushed
- autokeras
- Nov 25, 2025
- pytorch-meta
- Jul 17, 2023
Categories
- autokeras
- Developer Tools, Model Training
- pytorch-meta
- Model Training
Trust and health
Maintenance
- autokeras
- Slowing (36%)
- pytorch-meta
- Dormant (18%)
Days since push
- autokeras
- 309d
- pytorch-meta
- 1173d
Open issues (now)
- autokeras
- 161
- pytorch-meta
- 61
Stars delta
- autokeras
- +7 (30d)
- pytorch-meta
- -4 (30d)
Owner type
- autokeras
- Organization
- pytorch-meta
- User
Full report
- autokeras
- Trust report
- pytorch-meta
- Trust report
Shared compatibility
- Python · autokeras: Python runtime · pytorch-meta: Python runtime
Choose autokeras if…
- License: autokeras is Apache-2.0, pytorch-meta 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 pytorch-meta if…
- License: pytorch-meta is MIT, autokeras is Apache-2.0.
- Tags unique to pytorch-meta: data-loaders, extensions, few-shot-learning, meta-learning.
- When developing models that require handling few-shot learning scenarios where only a small amount of labeled data is available.
When NOT to use pytorch-meta
- If your project requires extensive support for traditional deep learning tasks, as PyTorch-Meta does not offer comprehensive utilities beyond few-shot learning and meta-learning.
- For those strictly adhering to a single ecosystem that does not include the PyTorch framework or its specific versions below 1.4.
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 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 (tristandeleu/pytorch-meta) · observed Oct 3, 2026
- GitHub forks (tristandeleu/pytorch-meta) · observed Oct 3, 2026
- Last push (tristandeleu/pytorch-meta) · observed Jul 17, 2023
- License file (MIT) · observed Oct 3, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: autokeras 9.3k · pytorch-meta 2.1k (synced Sep 30, 2026).
Common questions
- What is the difference between autokeras and pytorch-meta?
- autokeras: AutoML library for deep learning. pytorch-meta: Extensions and data-loaders for few-shot learning & meta-learning in PyTorch. See the comparison table for live GitHub stats and shared categories.
- When should I choose autokeras over pytorch-meta?
- Choose autokeras over pytorch-meta when License: autokeras is Apache-2.0, pytorch-meta 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 pytorch-meta over autokeras?
- Choose pytorch-meta over autokeras when License: pytorch-meta is MIT, autokeras is Apache-2.0; Tags unique to pytorch-meta: data-loaders, extensions, few-shot-learning, meta-learning; When developing models that require handling few-shot learning scenarios where only a small amount of labeled data is available.
- 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 pytorch-meta?
- If your project requires extensive support for traditional deep learning tasks, as PyTorch-Meta does not offer comprehensive utilities beyond few-shot learning and meta-learning. For those strictly adhering to a single ecosystem that does not include the PyTorch framework or its specific versions below 1.4.
- Is autokeras or pytorch-meta more popular on GitHub?
- autokeras has more GitHub stars (9,335 vs 2,058). Stars measure visibility, not whether either tool fits your constraints.
- Are autokeras and pytorch-meta open source?
- Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, pytorch-meta: MIT).
- Where can I find alternatives to autokeras or pytorch-meta?
- GraphCanon lists graph-backed alternatives at autokeras alternatives and pytorch-meta alternatives (autokeras markdown twin, pytorch-meta 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 pytorch-meta?
- autokeras: Slowing. pytorch-meta: 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 pytorch-meta?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autokeras trust report; pytorch-meta trust report.