docs.jax.dev · ML Frameworks
Composable transformations of NumPy style programs: automatic differentiation, JIT compilation and parallelism on GPUs and TPUs.
JAX is one of 20 ML framework tools on Axiomi. See all ML framework tools or how we check facts.
// guides
Tinygrad vs MLX compared for Apple silicon and beyond: hardware support, lazy graphs, JIT and compile, LLM tooling, install and which framework fits your project.
The best ML frameworks for Python in 2026, ranked by job: PyTorch, scikit-learn, JAX, Keras 3, XGBoost, LightGBM, TensorFlow, MLX and more, with versions.
Tinygrad vs PyTorch performance: when TinyJit and BEAM can outrun eager PyTorch, when torch.compile and the ecosystem win, and how to compare them fairly.
How to use TensorFlow in Python in 2026: install it in a venv, work with tensors and gradients, train a Keras model, feed data with tf.data and save it.
How to use TensorFlow with GPU in 2026: the pip [and-cuda] install on Linux and WSL2, Docker, Mac Metal, how to verify the GPU, and fixes for common errors.
TensorFlow vs PyTorch vs Keras in 2026: Keras 3 multibackend, which is easier to learn, open weight LLM ecosystem fit, and who should pick each stack.
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tinygradtinygrad.orgDeliberately small deep learning framework that aims to make it easy to add new accelerators.ML FrameworksOpen source★ 33.8k
TensorFlowtensorflow.orgGoogle's end to end machine learning platform, still widely deployed in production and on mobile via LiteRT.ML FrameworksOpen source★ 201.3k
Keraskeras.ioHigh level deep learning API that runs on JAX, TensorFlow or PyTorch backends.ML FrameworksOpen source★ 64.4k
MLXml-explore.github.ioApple's array framework for machine learning on Apple silicon, with unified memory and a NumPy style API.ML FrameworksOpen source★ 29k
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