Home/Compare/Auto-PyTorch vs MOE

Comparison

Auto-PyTorch vs MOE

Verdict

Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick MOE if mOE optimizes real-world metrics via automated black-box processes. It is written in C++.

Markdown twin · Auto-PyTorch alternatives · MOE alternatives

GraphCanon updated 2w

Auto-PyTorch logo

Auto-PyTorch

automl/Auto-PyTorch

2.5kpushed Apr 9, 2024
vs
MOE logo

MOE

YelpArchive/MOE

1.3kpushed Mar 24, 2023

Trust & integrity

SignalAuto-PyTorchMOE
Maintenance
Dormant (846d since push)
As of 2w · github_public_v1
Archived (1228d 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
Published findings
As of 1mo · osv@v1
Published findings
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

Auto-PyTorch
Automatic architecture search and hyperparameter optimization for PyTorch
MOE
A global, black box optimization engine for real world metric optimization

Stars

Auto-PyTorch
2.5k
MOE
1.3k

Forks

Auto-PyTorch
303
MOE
139

Open issues

Auto-PyTorch
75
MOE
175

Language

Auto-PyTorch
Python
MOE
C++

Adopt for

Auto-PyTorch
Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch.
MOE
MOE optimizes real-world metrics via automated black-box processes. It is written in C++.

Persona

Auto-PyTorch
-
MOE
-

Runtime

Auto-PyTorch
-
MOE
-

License

Auto-PyTorch
Apache-2.0
MOE
Licensed under the Apache License, Version 2.0.

Last pushed

Auto-PyTorch
Apr 9, 2024
MOE
Mar 24, 2023

Categories

Auto-PyTorch
Data & Retrieval, Model Training
MOE
Model Training

Trust and health

Maintenance

Auto-PyTorch
Dormant (18%)
MOE
Archived (8%)

Days since push

Auto-PyTorch
846d
MOE
1228d

Archived on GitHub

Auto-PyTorch
No
MOE
Yes

Open issues (now)

Auto-PyTorch
75
MOE
175

Full report

Auto-PyTorch
Trust report

Shared compatibility

  • Python · Auto-PyTorch: Python runtime · MOE: Python runtime

Choose Auto-PyTorch if…

  • Auto-PyTorch is primarily Python; MOE is C++.
  • License: Auto-PyTorch is Apache-2.0, MOE is Other.
  • Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data.
  • Also covers Data & Retrieval.
  • Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models.

When NOT to use Auto-PyTorch

  • Avoid using it if your AI development focuses on frameworks other than PyTorch.
  • Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning.

Choose MOE if…

  • MOE is primarily C++; Auto-PyTorch is Python.
  • License: MOE is Other, Auto-PyTorch is Apache-2.0.
  • Tags unique to MOE: c++, docker, rest server.
  • When you require an optimization engine that operates as a global, isolated system through Docker containers.

When NOT to use MOE

  • If your team lacks the knowledge or experience to configure and run Docker environments.
  • Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios.

Explore

Sources

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

GitHub stars on cards: Auto-PyTorch 2.5k · MOE 1.3k (synced Aug 4, 2026).

Common questions

What is the difference between Auto-PyTorch and MOE?
Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. MOE: A global, black box optimization engine for real world metric optimization. See the comparison table for live GitHub stats and shared categories.
When should I choose Auto-PyTorch over MOE?
Choose Auto-PyTorch over MOE when Auto-PyTorch is primarily Python; MOE is C++; License: Auto-PyTorch is Apache-2.0, MOE is Other; Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data; Also covers Data & Retrieval; Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models.
When should I choose MOE over Auto-PyTorch?
Choose MOE over Auto-PyTorch when MOE is primarily C++; Auto-PyTorch is Python; License: MOE is Other, Auto-PyTorch is Apache-2.0; Tags unique to MOE: c++, docker, rest server; When you require an optimization engine that operates as a global, isolated system through Docker containers.
When should I avoid Auto-PyTorch?
Avoid using it if your AI development focuses on frameworks other than PyTorch. Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning.
When should I avoid MOE?
If your team lacks the knowledge or experience to configure and run Docker environments. Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios.
Is Auto-PyTorch or MOE more popular on GitHub?
Auto-PyTorch has more GitHub stars (2,541 vs 1,321). Stars measure visibility, not whether either tool fits your constraints.
Are Auto-PyTorch and MOE open source?
Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, MOE: Other).
Where can I find alternatives to Auto-PyTorch or MOE?
GraphCanon lists graph-backed alternatives at Auto-PyTorch alternatives and MOE alternatives (Auto-PyTorch markdown twin, MOE 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, Auto-PyTorch or MOE?
Auto-PyTorch: Dormant. MOE: Archived. 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 Auto-PyTorch and MOE?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Auto-PyTorch trust report; MOE trust report.

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