The best TensorFlow alternatives

Apache TVM suits developers compiling pre-trained models for varied hardware and runtime targets.

The free plan is described for students, researchers, and hobbyists.

Gradient may suit individual ML/AI engineers, data scientists, researchers, teams, research groups, and startups building or serving machine learning…

It suits developers deploying machine-learning models across different hardware and environments, including browsers and mobile devices.

MegEngine may suit developers who want a framework spanning model development and deployment, from beginner tutorials to advanced workflows.

PyTorch suits developers, researchers, and enterprises building or deploying AI.

It suits professional Java developers building JVM deep-learning applications, importing models, training across clusters, or deploying to services…

Ludwig suits people building or tuning models across varied data types, from beginners using YAML or auto_train() to experts customizing PyTorch…

SINGA suits teams training deep-learning or machine-learning models who need distributed GPU training or on-premises deployment.

Caffe suits researchers, startups, and industrial teams building deep learning systems with configurable models and local or on-premises training.

MLX is designed for machine learning researchers, particularly those working with Apple silicon.