--- title: "autokeras vs katib" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-autokeras-vs-kubeflow-katib" tools: ["keras-team-autokeras", "kubeflow-katib"] --- # autokeras vs katib *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 katib if katib is an automated machine learning solution for Kubernetes environments, focused on hyperparameter tuning and neural architecture search. [autokeras](http://autokeras.com/) reports 9.3k GitHub stars, 1.4k forks, and 161 open issues, last pushed Nov 25, 2025. [katib](https://www.kubeflow.org/docs/components/katib) has 1.7k stars, 534 forks, and 106 open issues, last pushed Aug 4, 2026. Figures are from public GitHub metadata via [autokeras's repository](https://github.com/keras-team/autokeras) and [katib's repository](https://github.com/kubeflow/katib). | | [autokeras](/tools/keras-team-autokeras.md) | [katib](/tools/kubeflow-katib.md) | | --- | --- | --- | | Tagline | AutoML library for deep learning | Automated Machine Learning on Kubernetes | | Stars | 9,328 | 1,694 | | Forks | 1,393 | 534 | | Open issues | 161 | 106 | | 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+. | Katib is an automated machine learning solution for Kubernetes environments, focused on hyperparameter tuning and neural architecture search. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Developer Tools, Model Training | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [autokeras](/tools/keras-team-autokeras.md) | [katib](/tools/kubeflow-katib.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 251d | 0d | | Open issues (now) | 161 | 106 | | Full report | [trust report](/tools/keras-team-autokeras/trust.md) | [trust report](/tools/kubeflow-katib/trust.md) | ## Shared compatibility - **Python**: [autokeras](/tools/keras-team-autokeras.md) - Python runtime; [katib](/tools/kubeflow-katib.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: katib - **Adopt for:** Katib is an automated machine learning solution for Kubernetes environments, focused on hyperparameter tuning and neural architecture search. ## Choose when ### Choose autokeras if… - Tags unique to autokeras: autodl, deep-learning, keras, machine-learning. - Also covers Developer Tools. - When your project involves deep learning tasks requiring minimal manual intervention in designing models. ### Choose katib if… - Tags unique to katib: ai, hyperparameter-tuning. - Also covers Evaluation & Observability. - When you need to perform comprehensive hyperparameter tuning tasks within a Kubernetes cluster setup. ## 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 katib - Avoid using Katib if you do not have a Kubernetes cluster setup, as it heavily relies on this platform for operation. - If your project's requirements do not extend beyond simple model training tasks and you lack the resources to support a complex CI/CD pipeline like Kubeflow with Katib. - Not suitable when working in environments with strict constraints preventing the use of open-source tools under Apache-2.0 licenses. ## Common questions ### What is the difference between autokeras and katib? autokeras: AutoML library for deep learning. katib: Automated Machine Learning on Kubernetes. See the comparison table for live GitHub stats and shared categories. ### When should I choose autokeras over katib? Choose autokeras over katib when Tags unique to autokeras: autodl, deep-learning, keras, machine-learning; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models. ### When should I choose katib over autokeras? Choose katib over autokeras when Tags unique to katib: ai, hyperparameter-tuning; Also covers Evaluation & Observability; When you need to perform comprehensive hyperparameter tuning tasks within a Kubernetes cluster setup. ### 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 katib? Avoid using Katib if you do not have a Kubernetes cluster setup, as it heavily relies on this platform for operation. If your project's requirements do not extend beyond simple model training tasks and you lack the resources to support a complex CI/CD pipeline like Kubeflow with Katib. Not suitable when working in environments with strict constraints preventing the use of open-source tools under Apache-2.0 licenses. ### Is autokeras or katib more popular on GitHub? autokeras has more GitHub stars (9,328 vs 1,694). Stars measure visibility, not whether either tool fits your constraints. ### Are autokeras and katib open source? Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, katib: Apache-2.0). ### Where can I find alternatives to autokeras or katib? GraphCanon lists graph-backed alternatives at [autokeras alternatives](/tools/keras-team-autokeras/alternatives) and [katib alternatives](/tools/kubeflow-katib/alternatives) ([autokeras markdown twin](/tools/keras-team-autokeras/alternatives.md), [katib markdown twin](/tools/kubeflow-katib/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-kubeflow-katib.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, autokeras or katib? autokeras: Slowing. katib: 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 katib? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [autokeras trust report](/tools/keras-team-autokeras/trust); [katib trust report](/tools/kubeflow-katib/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/_