Comparison
HPOBench vs autoai
Verdict
Pick HPOBench if hPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios; pick autoai if python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation.
Markdown twin · HPOBench alternatives · autoai alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | HPOBench | autoai |
|---|---|---|
| Maintenance | Dormant (439d since push) As of 2w · github_public_v1 | Dormant (496d 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
- HPOBench
- A collection of hyperparameter optimization benchmark problems
- autoai
- Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation
Stars
- HPOBench
- 170
- autoai
- 186
Forks
- HPOBench
- 36
- autoai
- 46
Open issues
- HPOBench
- 34
- autoai
- 9
Language
- HPOBench
- Python
- autoai
- Python
Adopt for
- HPOBench
- HPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios.
- autoai
- Python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation.
Persona
- HPOBench
- -
- autoai
- -
Runtime
- HPOBench
- -
- autoai
- -
License
- HPOBench
- HPOBench is open source under the Apache-2.0 license.
- autoai
- Apache-2.0
Last pushed
- HPOBench
- May 21, 2025
- autoai
- Mar 25, 2025
Categories
- HPOBench
- Model Training
- autoai
- Model Training
Trust and health
Days since push
- HPOBench
- 439d
- autoai
- 496d
Open issues (now)
- HPOBench
- 34
- autoai
- 9
Full report
- HPOBench
- Trust report
- autoai
- Trust report
Shared compatibility
- Python · HPOBench: Python runtime · autoai: Python runtime
Choose HPOBench if…
- Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step..
- Tags unique to HPOBench: bayesian-optimization, benchmark, hyperparameter-optimization.
- When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments.
When NOT to use HPOBench
- Avoid HPOBench if your project does not require Python or you are looking for a platform that exclusively focuses on the automation of model selection without hyperparameter optimization.
- If you prefer tools with built-in support for multiple programming languages, rather than focusing solely on Python as is the case with HPOBench.
Choose autoai if…
- Tags unique to autoai: ai, autoai, codegen, deep-learning.
- Use AutoAI when you need a tool that can handle both regression and classification tasks specifically over numerical datasets.
- More GitHub stars (186 vs 170) - visibility, not fit.
When NOT to use autoai
- Avoid using AutoAI if your dataset includes non-numerical data exclusively as the framework is tailored for numerical data processing.
- Do not use if generating model training scripts in formats other than Jupyter Notebooks is required, as this tool only supports Python code output within a Jupyter format.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/HPOBench) · observed Aug 4, 2026
- GitHub forks (automl/HPOBench) · observed Aug 4, 2026
- Last push (automl/HPOBench) · observed May 21, 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 (blobcity/autoai) · observed Aug 4, 2026
- GitHub forks (blobcity/autoai) · observed Aug 4, 2026
- Last push (blobcity/autoai) · observed Mar 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 on cards: HPOBench 170 · autoai 186 (synced Aug 4, 2026).
Common questions
- What is the difference between HPOBench and autoai?
- HPOBench: A collection of hyperparameter optimization benchmark problems. autoai: Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation. See the comparison table for live GitHub stats and shared categories.
- When should I choose HPOBench over autoai?
- Choose HPOBench over autoai when Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step.; Tags unique to HPOBench: bayesian-optimization, benchmark, hyperparameter-optimization; When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments.
- When should I choose autoai over HPOBench?
- Choose autoai over HPOBench when Tags unique to autoai: ai, autoai, codegen, deep-learning; Use AutoAI when you need a tool that can handle both regression and classification tasks specifically over numerical datasets; More GitHub stars (186 vs 170) - visibility, not fit.
- When should I avoid HPOBench?
- Avoid HPOBench if your project does not require Python or you are looking for a platform that exclusively focuses on the automation of model selection without hyperparameter optimization. If you prefer tools with built-in support for multiple programming languages, rather than focusing solely on Python as is the case with HPOBench.
- When should I avoid autoai?
- Avoid using AutoAI if your dataset includes non-numerical data exclusively as the framework is tailored for numerical data processing. Do not use if generating model training scripts in formats other than Jupyter Notebooks is required, as this tool only supports Python code output within a Jupyter format.
- Is HPOBench or autoai more popular on GitHub?
- autoai has more GitHub stars (186 vs 170). Stars measure visibility, not whether either tool fits your constraints.
- Are HPOBench and autoai open source?
- Yes - both are open-source projects on GitHub (HPOBench: Apache-2.0, autoai: Apache-2.0).
- Where can I find alternatives to HPOBench or autoai?
- GraphCanon lists graph-backed alternatives at HPOBench alternatives and autoai alternatives (HPOBench markdown twin, autoai 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, HPOBench or autoai?
- HPOBench: Dormant. autoai: 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 HPOBench and autoai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: HPOBench trust report; autoai trust report.