Katib automates machine learning on Kubernetes, including hyperparameter tuning and neural architecture search.
The Best AutoKeras Alternatives in 2026
Looking for something like AutoKeras? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 24 are open source.
AutoKeras automates development of deep learning models through a machine learning library.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Katib | — | Yes | — |
| 2 | AutoGL | — | Yes | — |
| 3 | Archai | — | Yes | — |
| 4 | FEDOT | — | Yes | — |
| 5 | Petastorm | — | Yes | — |
| 6 | Guild AI | — | Yes | — |
| 7 | DeepSpeed | — | Yes | — |
| 8 | autoai | — | Yes | — |
| 9 | Learnergy | — | Yes | — |
| 10 | Detecto | — | Yes | — |
All AutoKeras alternatives
AutoGL provides automated graph learning through a machine learning framework and toolkit.
Archai supports neural architecture search with fast, reproducible, and modular research tools.
FEDOT automates machine learning model development through its modeling framework.
Enables single machine or distributed training and evaluation of deep learning models.
Guild AI automates and optimizes machine learning experiments while tracking each run.
DeepSpeed optimizes distributed training and inference for deep learning models.
autoai automates regression and classification modeling in Python through model search and hyperparameter tuning.
Use Learnergy, a Python library for training and working with energy-based machine learning models.
Detecto supports building and training computer vision models with the PyTorch machine learning framework.
ML_Forgex trains, evaluates, and predicts with machine learning models on cleaned datasets.
Auto_ViML builds multiple machine learning models with a single line of code.
m2cgen converts machine learning models into native code for multiple programming languages without runtime dependencies.
KerasTuner searches hyperparameters to optimize machine learning models built with Keras.
Lightwood builds and customizes machine learning pipelines using a declarative JSON-AI syntax.
EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions.
numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
PyTorch Geometric Temporal provides models and tools for spatiotemporal signal processing with neural learning.
PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
TensorFlow Model Optimization provides Keras and TensorFlow tools for model quantization and pruning.
Karate Club offers algorithms for unsupervised learning on graph data in Python.
This metric-learn repository contains Python implementations of metric learning algorithms.
metric-learn provides Python implementations of metric learning algorithms.
BayesO provides a Python package for Bayesian optimization algorithms and related modeling tasks.
Alternatives to similar tools
What is the best alternative to AutoKeras?
Are there open-source alternatives to AutoKeras?
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
























