NVIDIA TensorRT vs. vLLM Comparison


NVIDIA TensorRT NVIDIA	vLLM
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NVIDIA TensorRT	vLLM
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NVIDIA TensorRT: About NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.	vLLM: About vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.
NVIDIA TensorRT: Platforms Supported Windows Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	vLLM: Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
NVIDIA TensorRT: Audience Machine learning engineers and data scientists seeking a tool to optimize their deep learning operations	vLLM: Audience AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments
NVIDIA TensorRT: Support Phone Support Supported 24/7 Live Support Not Supported Online Supported	vLLM: Support Phone Support Not Supported 24/7 Live Support Supported Online Supported
NVIDIA TensorRT: API Offers API Supported	vLLM: API Offers API Supported
NVIDIA TensorRT: Screenshots and Videos View more images or videos	vLLM: Screenshots and Videos View more images or videos
NVIDIA TensorRT: Pricing Free Free Version Supported Free Trial Not Supported	vLLM: Pricing No information available. Free Version Not Supported Free Trial Not Supported
NVIDIA TensorRT: Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	vLLM: Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

NVIDIA TensorRT: Training Documentation Supported Webinars Supported Live Online Not Supported In Person Supported	vLLM: Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
NVIDIA TensorRT: Company Information NVIDIA Founded: 1993 United States developer.nvidia.com/tensorrt	vLLM: Company Information vLLM United States vllm.ai
NVIDIA TensorRT: Alternatives OpenVINO Intel	vLLM: Alternatives DeepInfer DeepSeek
NVIDIA TensorRT: NVIDIA Triton Inference Server NVIDIA	vLLM: LocalAI
NVIDIA TensorRT: NVIDIA DRIVE NVIDIA	vLLM: Ollama
NVIDIA TensorRT: TensorWave	vLLM: Wafer
NVIDIA TensorRT: Luminal View All	vLLM: NVIDIA TensorRT NVIDIA View All
NVIDIA TensorRT: Categories AI Inference Supported	vLLM: Categories AI Inference Supported

NVIDIA TensorRT: Integrations Hugging Face Supported NVIDIA DRIVE Supported PyTorch Supported Thunder Compute Supported Compute with Hivenet Not Supported DocsGPT Not Supported KServe Not Supported Kimi K2.5 Supported Kimi K2.7 Code Supported LFM3 Not Supported ModelLane Not Supported NVIDIA AI Enterprise Supported NVIDIA Jetson Supported NVIDIA Morpheus Supported NVIDIA virtual GPU Supported Nemotron 3.5 Super VL Not Supported OpenAI Not Supported RankLLM Supported Recursive Flint Not Supported TensorFlow Supported Show More Integrations View All 30 Integrations	vLLM: Integrations Hugging Face Supported NVIDIA DRIVE Supported PyTorch Supported Thunder Compute Supported Compute with Hivenet Supported DocsGPT Supported KServe Supported Kimi K2.5 Not Supported Kimi K2.7 Code Not Supported LFM3 Supported ModelLane Supported NVIDIA AI Enterprise Not Supported NVIDIA Jetson Not Supported NVIDIA Morpheus Not Supported NVIDIA virtual GPU Not Supported Nemotron 3.5 Super VL Supported OpenAI Supported RankLLM Not Supported Recursive Flint Supported TensorFlow Not Supported Show More Integrations View All 23 Integrations
NVIDIA TensorRT: Claim NVIDIA TensorRT and update features and information Claim NVIDIA TensorRT and update features and information	vLLM: Claim vLLM and update features and information Claim vLLM and update features and information