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TensorRT-LLM

NVIDIA's library for optimizing and serving LLMs on its GPUs.

TensorRT-LLM is NVIDIA's open-source library for compiling and running optimized LLM inference on NVIDIA GPUs. It provides a Python API to define and build highly tuned TensorRT engines with features like in-flight batching, paged KV caching, FP8/INT4 quantization, and tensor/pipeline parallelism. It pairs with the Triton Inference Server backend to deliver some of the lowest-latency LLM serving on NVIDIA hardware.

Repository

NVIDIA/TensorRT-LLM

Language

C++

What you'd build with it

  • Compiling LLMs into optimized TensorRT engines for the lowest latency on NVIDIA datacenter GPUs
  • Serving quantized (FP8/INT4) models with in-flight batching to maximize GPU throughput
  • Deploying multi-GPU LLM inference with tensor and pipeline parallelism behind Triton

Tags

servingnvidiagpuquantization