Comparison
HpBandSter vs autoai
Verdict
Pick HpBandSter if hpBandSter is noted for its robust approach to hyperparameter optimization and neural architecture search through distributed computing capabilities; 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 · HpBandSter alternatives · autoai alternatives
GraphCanon updated Oct 2, 2026
13views this month
Trust & integrity
| Signal | HpBandSter | autoai |
|---|---|---|
| Maintenance | Dormant (1446d since push) As of Oct 2, 2026 · github_public_v1 | Dormant (554d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 2, 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 | Published findings 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
- HpBandSter
- a distributed Hyperband implementation on Steroids
- autoai
- Python based framework for Automatic AI enabling model search, hyper-parameter tuning and Jupyter Notebook code generation
Stars
- HpBandSter
- 633
- autoai
- 186
Forks
- HpBandSter
- 106
- autoai
- 46
Open issues
- HpBandSter
- 66
- autoai
- 9
Language
- HpBandSter
- Python
- autoai
- Python
Adopt for
- HpBandSter
- HpBandSter is noted for its robust approach to hyperparameter optimization and neural architecture search through distributed computing capabilities.
- autoai
- Python based framework for automated machine learning focused on numerical data, providing model search, hyper-parameter tuning, and Jupyter Notebook code generation.
Persona
- HpBandSter
- -
- autoai
- -
Runtime
- HpBandSter
- -
- autoai
- -
License
- HpBandSter
- BSD-3-Clause License - Permits free use but requires preservation of copyright and license notices. Contributors retain the copyrights to their contributions.
- autoai
- Apache-2.0
Last pushed
- HpBandSter
- Oct 16, 2022
- autoai
- Mar 25, 2025
Categories
- HpBandSter
- Model Training
- autoai
- Model Training
Trust and health
Days since push
- HpBandSter
- 1446d
- autoai
- 554d
Open issues (now)
- HpBandSter
- 66
- autoai
- 9
Stars delta
- HpBandSter
- +1 (30d)
- autoai
- 0 (30d)
OSV dependency advisories
- HpBandSter
- No lockfile (source not queried)
- autoai
- Published findings
Full report
- HpBandSter
- Trust report
- autoai
- Trust report
Shared compatibility
- Python · HpBandSter: Python runtime · autoai: Python runtime
Choose HpBandSter if…
- License: HpBandSter is BSD-3-Clause, autoai is Apache-2.0.
- Pricing: HpBandSter is open-source software under a permissive BSD-3-Clause License, allowing unrestricted usage for personal or commercial purposes without any direct costs..
- Requirements: Min 4 GB RAM; Requires Python environment. No Docker required..
- Tags unique to HpBandSter: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, neural-architecture-search.
- HpBandSter is best used when conducting large-scale experiments on multiple machines that require efficient resource management across different environments.
When NOT to use HpBandSter
- If your project involves smaller datasets or less complex models where individual hyperparameter tuning can be done manually, HpBandSter might be an overkill due to its advanced distributed settings.
- Avoid using HpBandSter if you need a tool that heavily relies on Bayesian optimization techniques, as it specializes more in Hyperband methodology.
Choose autoai if…
- License: autoai is Apache-2.0, HpBandSter is BSD-3-Clause.
- 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.
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/HpBandSter) · observed Oct 2, 2026
- GitHub forks (automl/HpBandSter) · observed Oct 2, 2026
- Last push (automl/HpBandSter) · observed Oct 16, 2022
- License file (BSD-3-Clause) · observed Oct 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (blobcity/autoai) · observed Sep 30, 2026
- GitHub forks (blobcity/autoai) · observed Sep 30, 2026
- Last push (blobcity/autoai) · observed Mar 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: HpBandSter 633 · autoai 186 (synced Oct 2, 2026).
Common questions
- What is the difference between HpBandSter and autoai?
- HpBandSter: a distributed Hyperband implementation on Steroids. 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 HpBandSter over autoai?
- Choose HpBandSter over autoai when License: HpBandSter is BSD-3-Clause, autoai is Apache-2.0; Pricing: HpBandSter is open-source software under a permissive BSD-3-Clause License, allowing unrestricted usage for personal or commercial purposes without any direct costs.; Requirements: Min 4 GB RAM; Requires Python environment. No Docker required.; Tags unique to HpBandSter: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, neural-architecture-search; HpBandSter is best used when conducting large-scale experiments on multiple machines that require efficient resource management across different environments.
- When should I choose autoai over HpBandSter?
- Choose autoai over HpBandSter when License: autoai is Apache-2.0, HpBandSter is BSD-3-Clause; 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.
- When should I avoid HpBandSter?
- If your project involves smaller datasets or less complex models where individual hyperparameter tuning can be done manually, HpBandSter might be an overkill due to its advanced distributed settings. Avoid using HpBandSter if you need a tool that heavily relies on Bayesian optimization techniques, as it specializes more in Hyperband methodology.
- 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 HpBandSter or autoai more popular on GitHub?
- HpBandSter has more GitHub stars (633 vs 186). Stars measure visibility, not whether either tool fits your constraints.
- Are HpBandSter and autoai open source?
- Yes - both are open-source projects on GitHub (HpBandSter: BSD-3-Clause, autoai: Apache-2.0).
- Where can I find alternatives to HpBandSter or autoai?
- GraphCanon lists graph-backed alternatives at HpBandSter alternatives and autoai alternatives (HpBandSter 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, HpBandSter or autoai?
- HpBandSter: 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 HpBandSter and autoai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: HpBandSter trust report; autoai trust report.