--- title: "autokeras vs optuna" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-autokeras-vs-optuna-optuna" tools: ["keras-team-autokeras", "optuna-optuna"] --- # autokeras vs optuna *GraphCanon updated Aug 4, 2026* ## Verdict 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+; pick optuna if optuna automates hyperparameter tuning in Python, integrating seamlessly with major ML frameworks. [autokeras](http://autokeras.com/) reports 9.3k GitHub stars, 1.4k forks, and 161 open issues, last pushed Nov 25, 2025. [optuna](https://optuna.org) has 15k stars, 1.4k forks, and 16 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [autokeras's repository](https://github.com/keras-team/autokeras) and [optuna's repository](https://github.com/optuna/optuna). | | [autokeras](/tools/keras-team-autokeras.md) | [optuna](/tools/optuna-optuna.md) | | --- | --- | --- | | Tagline | AutoML library for deep learning | A hyperparameter optimization framework | | Stars | 9,328 | 14,603 | | Forks | 1,393 | 1,361 | | Open issues | 161 | 16 | | Language | Python | Python | | 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+. | Optuna automates hyperparameter tuning in Python, integrating seamlessly with major ML frameworks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Developer Tools, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autokeras](/tools/keras-team-autokeras.md) | [optuna](/tools/optuna-optuna.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 251d | 1d | | Open issues (now) | 161 | 16 | | Full report | [trust report](/tools/keras-team-autokeras/trust.md) | [trust report](/tools/optuna-optuna/trust.md) | ## Shared compatibility - **Python**: [autokeras](/tools/keras-team-autokeras.md) - Python runtime; [optuna](/tools/optuna-optuna.md) - Python runtime ## 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+. ## Decision facts: optuna - **Adopt for:** Optuna automates hyperparameter tuning in Python, integrating seamlessly with major ML frameworks. ## Choose when ### Choose autokeras if… - License: autokeras is Apache-2.0, optuna is MIT. - 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. ### Choose optuna if… - License: optuna is MIT, autokeras is Apache-2.0. - Tags unique to optuna: distributed, hyperparameter-optimization, parallel, python. - When you need to streamline the hyperparameter tuning process for machine learning models built in Python. ## 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. ## When NOT to use optuna - If your project is not compatible with Python, as Optuna does not support other languages directly out of box. - Projects requiring manual control over every aspect of hyperparameter tuning might find Optuna too automated for their needs. ## Common questions ### What is the difference between autokeras and optuna? autokeras: AutoML library for deep learning. optuna: A hyperparameter optimization framework. See the comparison table for live GitHub stats and shared categories. ### When should I choose autokeras over optuna? Choose autokeras over optuna when License: autokeras is Apache-2.0, optuna is MIT; 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 choose optuna over autokeras? Choose optuna over autokeras when License: optuna is MIT, autokeras is Apache-2.0; Tags unique to optuna: distributed, hyperparameter-optimization, parallel, python; When you need to streamline the hyperparameter tuning process for machine learning models built in Python. ### 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. ### When should I avoid optuna? If your project is not compatible with Python, as Optuna does not support other languages directly out of box. Projects requiring manual control over every aspect of hyperparameter tuning might find Optuna too automated for their needs. ### Is autokeras or optuna more popular on GitHub? optuna has more GitHub stars (14,603 vs 9,328). Stars measure visibility, not whether either tool fits your constraints. ### Are autokeras and optuna open source? Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, optuna: MIT). ### Where can I find alternatives to autokeras or optuna? GraphCanon lists graph-backed alternatives at [autokeras alternatives](/tools/keras-team-autokeras/alternatives) and [optuna alternatives](/tools/optuna-optuna/alternatives) ([autokeras markdown twin](/tools/keras-team-autokeras/alternatives.md), [optuna markdown twin](/tools/optuna-optuna/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/keras-team-autokeras-vs-optuna-optuna.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autokeras or optuna? autokeras: Slowing. optuna: Very active. 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 autokeras and optuna? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autokeras trust report](/tools/keras-team-autokeras/trust); [optuna trust report](/tools/optuna-optuna/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=keras-team-autokeras`](/api/graphcanon/graph?tool=keras-team-autokeras) - 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/_