Home/Compare/vega vs autokeras

Comparison

vega vs autokeras

Verdict

Pick vega if vega is an AutoML toolchain from Huawei Noah's Ark Lab that streamlines model building and selection with Python; 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 · vega alternatives · autokeras alternatives

GraphCanon updated 2w

vega logo

vega

huawei-noah/vega

849pushed Feb 15, 2023
vs
autokeras logo

autokeras

keras-team/autokeras

9.3kpushed Nov 25, 2025

Trust & integrity

Signalvegaautokeras
Maintenance
Dormant (1266d since push)
As of 2w · github_public_v1
Slowing (251d 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
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

vega
AutoML tools chain
autokeras
AutoML library for deep learning

Stars

vega
849
autokeras
9.3k

Forks

vega
177
autokeras
1.4k

Open issues

vega
53
autokeras
161

Language

vega
Python
autokeras
Python

Adopt for

vega
Vega is an AutoML toolchain from Huawei Noah's Ark Lab that streamlines model building and selection with Python.
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

vega
-
autokeras
-

Runtime

vega
-
autokeras
-

License

vega
Other
autokeras
Apache-2.0

Last pushed

vega
Feb 15, 2023
autokeras
Nov 25, 2025

Categories

vega
Model Training
autokeras
Developer Tools, Model Training

Trust and health

Maintenance

vega
Dormant (18%)
autokeras
Slowing (36%)

Days since push

vega
1266d
autokeras
251d

Open issues (now)

vega
53
autokeras
161

Full report

autokeras
Trust report

Choose vega if…

  • License: vega is Other, autokeras is Apache-2.0.
  • When leveraging the specific optimizations offered by Huawei Noah's Ark Lab in your automated machine learning workflows
  • Leaner open-issue backlog (53).

When NOT to use vega

  • If dependency on proprietary solutions, such as those from a single vendor like Huawei, needs to be avoided
  • When you require an extensive open community support or the flexibility traditionally offered by more established open-source AutoML tools

Choose autokeras if…

  • License: autokeras is Apache-2.0, vega is Other.
  • Tags unique to autokeras: autodl, deep-learning, keras, machine-learning.
  • 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 on cards: vega 849 · autokeras 9.3k (synced Aug 4, 2026).

Common questions

What is the difference between vega and autokeras?
vega: AutoML tools chain. autokeras: AutoML library for deep learning. See the comparison table for live GitHub stats and shared categories.
When should I choose vega over autokeras?
Choose vega over autokeras when License: vega is Other, autokeras is Apache-2.0; When leveraging the specific optimizations offered by Huawei Noah's Ark Lab in your automated machine learning workflows; Leaner open-issue backlog (53).
When should I choose autokeras over vega?
Choose autokeras over vega when License: autokeras is Apache-2.0, vega is Other; Tags unique to autokeras: autodl, deep-learning, keras, machine-learning; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models.
When should I avoid vega?
If dependency on proprietary solutions, such as those from a single vendor like Huawei, needs to be avoided When you require an extensive open community support or the flexibility traditionally offered by more established open-source AutoML tools
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 vega or autokeras more popular on GitHub?
autokeras has more GitHub stars (9,328 vs 849). Stars measure visibility, not whether either tool fits your constraints.
Are vega and autokeras open source?
Yes - both are open-source projects on GitHub (vega: Other, autokeras: Apache-2.0).
Where can I find alternatives to vega or autokeras?
GraphCanon lists graph-backed alternatives at vega alternatives and autokeras alternatives (vega 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, vega or autokeras?
vega: Dormant. 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 vega and autokeras?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: vega trust report; autokeras trust report.

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