VoiceStudio is the open-source, fully-local ElevenLabs alternative โ voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages.
Local AI BGM and sound effects for Claude Code and any MCP client. Stable Audio 3 on Apple Silicon (MLX) and Windows NVIDIA GPUs (PyTorch). No cloud, no API key.
Fish Audio Drama 3 text-to-speech on the TensorFold native CUDA engine for DGX Spark (GB10): recipe, engine patches, benchmarks. Built with Fish Audio.
Qwen3.8-Flash-Next (180B MoE) on one 12-16 GB NVIDIA GPU, Linux or Windows. Own engine, own compression.
A high-throughput and memory-efficient inference and serving engine for LLMs
The open-source AI voice studio. Clone, dictate, create.
SGLang is a high-performance serving framework for large language models and multimodal models.
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.
The most powerful local music generation model that outperforms almost all commercial alternatives, supporting Mac, AMD, Intel, and CUDA devices.
NumPy & SciPy for GPU
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
NumPy aware dynamic Python compiler using LLVM
LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.
A Python framework for GPU-accelerated simulation, robotics, and machine learning.
A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.
NVIDIA cuML: GPU-Accelerated Machine Learning
A PyTorch Library for Accelerating 3D Deep Learning Research
AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
Agent Skills for NVIDIA products โ install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.
Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.
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.
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
Cross-platform text editor, written in Free Pascal
RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
PyTorch native quantization for training and inference
Pytorch domain library for recommendation systems
Community recipes for serving LLMs on RTX 3090/4090/5090 CUDA gpus. Multi-engine (vLLM, sglang, llama.cpp and other custom engines) and model-agnostic. Currently shipping Qwen3.8-27B Qwen3.6 35B Gemma 4 26B Gemma 4 31B configs for 1ร/2ร/4x/8x cards.
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.
A deep learning package for many-body potential energy representation and molecular dynamics
CUDA integration for Python, plus shiny features
๐ค A Python library for learning and evaluating knowledge graph embeddings
Open Source AI Accelerator Research Platform Standard / ๅผๆบๆจ็็ ็ฉถๅนณๅฐ
Large-scale LLM inference engine
:metal: TT-NN operator library, and TT-Metalium low level kernel programming model.
SGLang-Omni is a high-performance serving framework for audio models (TTS, ASR) and unified multimodal models.
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
Kernel Design Agents (KDA) is a agent-centric workflow to write high-performance CUDA Kernels.
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
OpenCL integration for Python, plus shiny features
cuDNN Frontend is NVIDIA's modern, open-source entry point to the cuDNN library and a growing collection of high-performance open-source kernels.
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms
GPU-accelerated homomorphic encryption in Python: Paillier and BFV, with encrypted nearest-neighbour search. Experimental research code.
gprMax is open source software that simulates electromagnetic wave propagation using the Finite-Difference Time-Domain Finite-Difference (FDTD) code for numerical modelling of Ground Penetrating Radar (GPR), antennas, radar and bioelectromagnetics
Python Computer Vision & Video Analytics Framework With Batteries Included
SOMA: Unifying Parametric Human Body Models
High-performance Vision library in Python. Scale your research, not boilerplate.
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, Gaudi NPU, Google TPU, GraphCore IPU and other NPUs.
An app and guide to easily configure Windows, Linux, MacOS, Google TV, Stremio, Home Assistant and more (including WSL2, GPU drivers & development tools). Improve your UX & productivity.
A code generator for array-based code on CPUs and GPUs
DaCe - Data Centric Parallel Programming
Radar Simulator built with Python and C++
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
From teacher to tiles โ a from-scratch LLM distillation & serving engine: custom Triton/CUDA kernels, FSDP distillation, paged-KV continuous batching, speculative decoding, a Rust gateway, a JAX oracle, and interpretability tooling.
CUDA kernels for linear attention variants, written in CuTe DSL and CUTLASS C++.
Windows ๆฌๅฐๅคๆจกๆ AI ๆก้ขๆกๅฎ ๏ผๆฏๆๅฑๅนไธ้ณ้ขๆ็ฅใ
Real-time multimodal desktop agent evolving toward a persistent AI OS interface (0.17 ฮฑ).
Run CUDA-targeted Windows applications on AMD GPUs with ZLUDA + ROCm/HIP.
Phonon: open speech recognition models (Phonon-2, Phonon-1) โ CLI, CPU and CUDA images