--- title: "autokeras vs MOE" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-autokeras-vs-yelparchive-moe" tools: ["keras-team-autokeras", "yelparchive-moe"] --- # autokeras vs MOE *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 MOE if mOE optimizes real-world metrics via automated black-box processes. It is written in C++. [autokeras](http://autokeras.com/) reports 9.3k GitHub stars, 1.4k forks, and 161 open issues, last pushed Nov 25, 2025. [MOE](https://github.com/YelpArchive/MOE) has 1.3k stars, 139 forks, and 175 open issues, last pushed Mar 24, 2023. Figures are from public GitHub metadata via [autokeras's repository](https://github.com/keras-team/autokeras) and [MOE's repository](https://github.com/YelpArchive/MOE). | | [autokeras](/tools/keras-team-autokeras.md) | [MOE](/tools/yelparchive-moe.md) | | --- | --- | --- | | Tagline | AutoML library for deep learning | A global, black box optimization engine for real world metric optimization | | Stars | 9,328 | 1,321 | | Forks | 1,393 | 139 | | Open issues | 161 | 175 | | Language | Python | C++ | | 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+. | MOE optimizes real-world metrics via automated black-box processes. It is written in C++. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Licensed under the Apache License, Version 2.0. | | 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) | [MOE](/tools/yelparchive-moe.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Archived (8%) | | Days since push | 251d | 1228d | | Archived on GitHub | No | Yes | | Open issues (now) | 161 | 175 | | Full report | [trust report](/tools/keras-team-autokeras/trust.md) | [trust report](/tools/yelparchive-moe/trust.md) | ## Shared compatibility - **Python**: [autokeras](/tools/keras-team-autokeras.md) - Python runtime; [MOE](/tools/yelparchive-moe.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: MOE - **Adopt for:** MOE optimizes real-world metrics via automated black-box processes. It is written in C++. - **License detail:** Licensed under the Apache License, Version 2.0. ## Choose when ### Choose autokeras if… - autokeras is primarily Python; MOE is C++. - License: autokeras is Apache-2.0, MOE 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. ### Choose MOE if… - MOE is primarily C++; autokeras is Python. - License: MOE is Other, autokeras is Apache-2.0. - Tags unique to MOE: c++, docker, rest server. - MOE ships Docker support for self-hosted deployment. - When you require an optimization engine that operates as a global, isolated system through Docker containers. ## 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 MOE - If your team lacks the knowledge or experience to configure and run Docker environments. - Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios. ## Common questions ### What is the difference between autokeras and MOE? autokeras: AutoML library for deep learning. MOE: A global, black box optimization engine for real world metric optimization. See the comparison table for live GitHub stats and shared categories. ### When should I choose autokeras over MOE? Choose autokeras over MOE when autokeras is primarily Python; MOE is C++; License: autokeras is Apache-2.0, MOE 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 choose MOE over autokeras? Choose MOE over autokeras when MOE is primarily C++; autokeras is Python; License: MOE is Other, autokeras is Apache-2.0; Tags unique to MOE: c++, docker, rest server; MOE ships Docker support for self-hosted deployment; When you require an optimization engine that operates as a global, isolated system through Docker containers. ### 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 MOE? If your team lacks the knowledge or experience to configure and run Docker environments. Not suitable for projects where real-time interaction with optimization processes is needed, as MOE focuses on batch processing scenarios. ### Is autokeras or MOE more popular on GitHub? autokeras has more GitHub stars (9,328 vs 1,321). Stars measure visibility, not whether either tool fits your constraints. ### Are autokeras and MOE open source? Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, MOE: Other). ### Where can I find alternatives to autokeras or MOE? GraphCanon lists graph-backed alternatives at [autokeras alternatives](/tools/keras-team-autokeras/alternatives) and [MOE alternatives](/tools/yelparchive-moe/alternatives) ([autokeras markdown twin](/tools/keras-team-autokeras/alternatives.md), [MOE markdown twin](/tools/yelparchive-moe/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-yelparchive-moe.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autokeras or MOE? autokeras: Slowing. MOE: Archived. 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 MOE? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autokeras trust report](/tools/keras-team-autokeras/trust); [MOE trust report](/tools/yelparchive-moe/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/_