The Best TensorFlow Alternatives in 2026

Curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning.

Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.

QKeras provides quantization tools for deep learning with TensorFlow Keras.

The open source Feast feature store lets teams define, manage, discover, and serve features for machine learning.

Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.

Sagify describes its project as a way to work with large language models and machine learning more easily.

TPOT uses genetic programming to optimize machine learning pipelines in Python.

ORMB packages machine learning models as OCI artifacts, in a workflow described as Docker for ML models.

Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.

Cog packages machine learning models into containers to support deployment across environments.

The Datumbox framework is written in Java for developing machine learning and statistical applications.

The linfa project provides a machine learning framework written in Rust.

Hypernets offers a general automated machine learning framework for developing end to end AutoML toolkits in specific domains.

MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.

FLAML provides a fast Python library for automated machine learning and tuning.

A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.

The Feast repository describes an open source feature store for AI and machine learning projects.

Kubeflow provides a machine learning toolkit for deploying workflows on Kubernetes.

The Hydrosphere repository describes an MLOps platform for machine learning operations.

Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.

The fuku-ml project provides a machine learning library described as simple to use.

ModelDB tracks machine learning model versions, metadata, and experiments.

FlexML offers an easy to use and flexible automated machine learning library for Python.

Kedro-Viz visualizes Kedro data and machine learning pipelines and tracks experiments.