The best MLX alternatives
The rest of Best Deep Learning Software, in this site's order: each with what it costs, where it runs and its record score.
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.
TensorFlow suits developers building machine learning models for servers, edge devices, or the web.
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.