--- title: "HPOBench vs rembo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automl-hpobench-vs-ziyuw-rembo" tools: ["automl-hpobench", "ziyuw-rembo"] --- # HPOBench vs rembo *GraphCanon updated Aug 4, 2026* ## Verdict Pick HPOBench if hPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios; pick rembo if rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. [HPOBench](https://github.com/automl/HPOBench) reports 170 GitHub stars, 36 forks, and 34 open issues, last pushed May 21, 2025. [rembo](https://github.com/ziyuw/rembo) has 117 stars, 25 forks, and 3 open issues, last pushed Aug 4, 2013. Figures are from public GitHub metadata via [HPOBench's repository](https://github.com/automl/HPOBench) and [rembo's repository](https://github.com/ziyuw/rembo). | | [HPOBench](/tools/automl-hpobench.md) | [rembo](/tools/ziyuw-rembo.md) | | --- | --- | --- | | Tagline | A collection of hyperparameter optimization benchmark problems | Bayesian optimization in high-dimensions via random embedding. | | Stars | 170 | 117 | | Forks | 36 | 25 | | Open issues | 34 | 3 | | Language | Python | Matlab | | Adopt for | HPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios. | Rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. | | Persona | - | - | | Runtime | - | - | | License | HPOBench is open source under the Apache-2.0 license. | - | | Categories | Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [HPOBench](/tools/automl-hpobench.md) | [rembo](/tools/ziyuw-rembo.md) | | --- | --- | --- | | Days since push | 439d | 4747d | | Open issues (now) | 34 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/automl-hpobench/trust.md) | [trust report](/tools/ziyuw-rembo/trust.md) | ## Decision facts: HPOBench - **Pricing:** freemium - **Requirements:** The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step. - **Adopt for:** HPOBench is useful for researchers and developers working on hyperparameter optimization techniques in automated machine learning scenarios. - **License detail:** HPOBench is open source under the Apache-2.0 license. ## Decision facts: rembo - **Adopt for:** Rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. ## Choose when ### Choose HPOBench if… - HPOBench is primarily Python; rembo is Matlab. - Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step.. - Tags unique to HPOBench: automl, benchmark, hyperparameter-optimization, python. - When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments. ### Choose rembo if… - rembo is primarily Matlab; HPOBench is Python. - Tags unique to rembo: high-dimensional space, random embedding. - When working with high-dimensional data spaces that require efficient exploration and optimization, making it ideal for problems exceeding typical dimensions ## 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. ## When NOT to use rembo - For low-dimensional spaces where full Bayesian optimization methods would be more efficient and less complex than random embedding - In scenarios requiring open-source or licensed software when Rembo's license status is unknown, potentially limiting its use in certain projects ## Common questions ### What is the difference between HPOBench and rembo? HPOBench: A collection of hyperparameter optimization benchmark problems. rembo: Bayesian optimization in high-dimensions via random embedding.. See the comparison table for live GitHub stats and shared categories. ### When should I choose HPOBench over rembo? Choose HPOBench over rembo when HPOBench is primarily Python; rembo is Matlab; Requirements: The installation recommends, but does not strictly require singularity version 3.6, which can be an additional setup step.; Tags unique to HPOBench: automl, benchmark, hyperparameter-optimization, python; When you are specifically interested in benchmarking hyperparameter optimization problems that include containerized benchmarks to ensure consistency across environments. ### When should I choose rembo over HPOBench? Choose rembo over HPOBench when rembo is primarily Matlab; HPOBench is Python; Tags unique to rembo: high-dimensional space, random embedding; When working with high-dimensional data spaces that require efficient exploration and optimization, making it ideal for problems exceeding typical dimensions. ### 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 rembo? For low-dimensional spaces where full Bayesian optimization methods would be more efficient and less complex than random embedding In scenarios requiring open-source or licensed software when Rembo's license status is unknown, potentially limiting its use in certain projects ### Is HPOBench or rembo more popular on GitHub? HPOBench has more GitHub stars (170 vs 117). Stars measure visibility, not whether either tool fits your constraints. ### Are HPOBench and rembo open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to HPOBench or rembo? GraphCanon lists graph-backed alternatives at [HPOBench alternatives](/tools/automl-hpobench/alternatives) and [rembo alternatives](/tools/ziyuw-rembo/alternatives) ([HPOBench markdown twin](/tools/automl-hpobench/alternatives.md), [rembo markdown twin](/tools/ziyuw-rembo/alternatives.md)), 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](/compare/automl-hpobench-vs-ziyuw-rembo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, HPOBench or rembo? HPOBench: Dormant. rembo: 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 rembo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [HPOBench trust report](/tools/automl-hpobench/trust); [rembo trust report](/tools/ziyuw-rembo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automl-hpobench`](/api/graphcanon/graph?tool=automl-hpobench) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_