jax-ml/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Frontier-class open models on a free Kaggle TPU v5e-8: GLM-5.3-Flash 320B MoE (~64 tok/s, our own JAX engine) and Qwen3.8-27B bf16 (~130 tok/s), 262k context, prefix caching. Works with Claude Code, Codex, opencode and pi.
Distributed AI Model Training and LLM Fine-Tuning on Kubernetes
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.
🏔️ ALPS: Visual State Encoders for World Models
A simple, performant, and scalable Jax LLM!
a rust-native Modelica compiler for fast, composable, scientific computing
Deep Learning for humans
A retargetable MLIR-based machine learning compiler and runtime toolkit.
A deep learning package for many-body potential energy representation and molecular dynamics
Digital Audio Workstation with Python; VST instruments/effects, parameter automation, FAUST, JAX, Warp Markers, and JUCE processors
Mastering Diverse Domains through World Models
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Machine learning algorithms for many-body quantum systems
Pretrained model hub for Keras 3.
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Probabilistic Programming and Nested sampling in JAX
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Functional programming language for signal processing and sound synthesis
Orbax provides common checkpointing and persistence utilities for JAX users
Library for reading and processing ML training data.
Gaussian processes in JAX and Equinox.
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Gaussian processes in JAX and Equinox.
Convert Machine Learning Code Between Frameworks
Monte Carlo tree search in JAX
Open finite element infrastructure for nonlinear computational mechanics.
Universal Python SDK to run AI workloads on Kubernetes
TensorLy: Tensor Learning in Python.
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