--- title: "hyperopt vs autokeras" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hyperopt-hyperopt-vs-keras-team-autokeras" tools: ["hyperopt-hyperopt", "keras-team-autokeras"] --- # hyperopt vs autokeras *GraphCanon updated Aug 4, 2026* ## Verdict Pick hyperopt if hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing; 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+. [hyperopt](http://hyperopt.github.io/hyperopt) reports 7.6k GitHub stars, 1.1k forks, and 9 open issues, last pushed Aug 3, 2026. [autokeras](http://autokeras.com/) has 9.3k stars, 1.4k forks, and 161 open issues, last pushed Nov 25, 2025. Figures are from public GitHub metadata via [hyperopt's repository](https://github.com/hyperopt/hyperopt) and [autokeras's repository](https://github.com/keras-team/autokeras). | | [hyperopt](/tools/hyperopt-hyperopt.md) | [autokeras](/tools/keras-team-autokeras.md) | | --- | --- | --- | | Tagline | Distributed Asynchronous Hyperparameter Optimization in Python | AutoML library for deep learning | | Stars | 7,598 | 9,328 | | Forks | 1,075 | 1,393 | | Open issues | 9 | 161 | | Language | Python | Python | | Adopt for | Hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing. | AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | Model Training | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hyperopt](/tools/hyperopt-hyperopt.md) | [autokeras](/tools/keras-team-autokeras.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 251d | | Open issues (now) | 9 | 161 | | Full report | [trust report](/tools/hyperopt-hyperopt/trust.md) | [trust report](/tools/keras-team-autokeras/trust.md) | ## Shared compatibility - **Python**: [hyperopt](/tools/hyperopt-hyperopt.md) - Python runtime; [autokeras](/tools/keras-team-autokeras.md) - Python runtime ## Decision facts: hyperopt - **Adopt for:** Hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing. ## Decision facts: autokeras - **Adopt for:** AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+. ## Choose when ### Choose hyperopt if… - License: hyperopt is Other, autokeras is Apache-2.0. - Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization. - When you need to optimize machine learning model parameters on a distributed system asynchronously. ### Choose autokeras if… - License: autokeras is Apache-2.0, hyperopt is Other. - Tags unique to autokeras: autodl, automl, deep-learning, keras. - Also covers Developer Tools. - When your project involves deep learning tasks requiring minimal manual intervention in designing models. ## When NOT to use hyperopt - If your project does not support asynchronous execution, opting for synchronous tools might be more suitable. - Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options. ## 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. ## Common questions ### What is the difference between hyperopt and autokeras? hyperopt: Distributed Asynchronous Hyperparameter Optimization in Python. autokeras: AutoML library for deep learning. See the comparison table for live GitHub stats and shared categories. ### When should I choose hyperopt over autokeras? Choose hyperopt over autokeras when License: hyperopt is Other, autokeras is Apache-2.0; Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization; When you need to optimize machine learning model parameters on a distributed system asynchronously. ### When should I choose autokeras over hyperopt? Choose autokeras over hyperopt when License: autokeras is Apache-2.0, hyperopt is Other; Tags unique to autokeras: autodl, automl, deep-learning, keras; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models. ### When should I avoid hyperopt? If your project does not support asynchronous execution, opting for synchronous tools might be more suitable. Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options. ### 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 hyperopt or autokeras more popular on GitHub? autokeras has more GitHub stars (9,328 vs 7,598). Stars measure visibility, not whether either tool fits your constraints. ### Are hyperopt and autokeras open source? Yes - both are open-source projects on GitHub (hyperopt: Other, autokeras: Apache-2.0). ### Where can I find alternatives to hyperopt or autokeras? GraphCanon lists graph-backed alternatives at [hyperopt alternatives](/tools/hyperopt-hyperopt/alternatives) and [autokeras alternatives](/tools/keras-team-autokeras/alternatives) ([hyperopt markdown twin](/tools/hyperopt-hyperopt/alternatives.md), [autokeras markdown twin](/tools/keras-team-autokeras/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/hyperopt-hyperopt-vs-keras-team-autokeras.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hyperopt or autokeras? hyperopt: Very active. 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 hyperopt and autokeras? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hyperopt trust report](/tools/hyperopt-hyperopt/trust); [autokeras trust report](/tools/keras-team-autokeras/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hyperopt-hyperopt`](/api/graphcanon/graph?tool=hyperopt-hyperopt) - 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/_