1.vllm-project / vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
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13 repositories by Attention Score · Oct 4, 2026 – Nov 2, 2026 (UTC)
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.
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.
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
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.
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.
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.
NumPy & SciPy for GPU
NumPy aware dynamic Python compiler using LLVM
NVIDIA cuML: GPU-Accelerated Machine Learning
A PyTorch Library for Accelerating 3D Deep Learning Research