Tensors and Dynamic neural networks in Python with strong GPU acceleration
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AI agents running research on single-GPU nanochat training automatically
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
If you live in the terminal, kitty is made for you! Cross-platform, fast, feature-rich, GPU based.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Machine Learning Engineering Open Book
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
Open Machine Learning Compiler Framework
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
NumPy & SciPy for GPU
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
《深入理解 AI Infra：量化分析与系统设计》（李博杰 著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验
High-performance TensorFlow library for quantitative finance.
NVIDIA cuML: GPU-Accelerated Machine Learning
A highly efficient implementation of Gaussian Processes in PyTorch
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
The animation engine for agents: blazingly fast math and 3D videos with Manim's Python API, on a Rust GPU core.
GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard | Fable 5 Level Coding for a Fifth the Price - or on a Single GPU