A high-throughput and memory-efficient inference and serving engine for LLMs
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Run frontier AI locally.
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
SGLang is a high-performance serving framework for large language models and multimodal models.
Universal LLM Deployment Engine with ML Compilation
- llm
- machine-learning-compilation
- language-model
- tvm
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.
FauxPilot - an open-source alternative to GitHub Copilot server
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
- llm
- llmops
- model-inference
- fine-tuning
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.
- kv-cache
- llm-inference
- local-llm
- quantization
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
- agents
- calibration
- classification
- decision-making
Official Inference Code of EAGLE-4
- eagle
- gpu
- llm-inference
- sglang
EdgeRock: Strong Reasoning at Constant Memory. Multimodal models with O(N) generation and O(1) persistent history. Inference and evaluation code.
Native vLLM serving for Jev decision models
Run many AI agents at once on your Mac, up to 3x faster.
- agents
- apple-silicon
- artificial-intelligence
- inference-acceleration
DeepSeek-V4.1-Flash-1017 EXL3 on 2x DGX Sparks with TensorFold
🧱 Experimental library for building inference engines
Fast, exact inference for StartLux-Decision models on NVIDIA GPUs: the released GGUF files on int8 and 4-bit tensor cores, behind the /v1/systemone API, with up to 5.3× lower latency than vLLM in FP8 and bit-identical answers.
- calibration
- cuda
- cuda-graphs
- decision-making
Official implementation of paper "Cache Engineering for Agents"