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TensorRT-LLM

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.

llm-action

This project aims to share the technical principles and practical experience related to large models (large model engineering, large model application implementation)

Popularity
Repository stars14,99525,243Highest
7-day net stars——
Fork2,901Highest2,858
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2026-11-032026-10-14
Maintenance notesNot verifiedNot verified
Repository created2023-08-162023-05-23
License & use
LicenseLicense not declaredApache-2.0 · Permissive
License sourceLicense sourceLicense source
PricingPricing not verifiedPricing not verified
Basics
Browse by purposeModel servingModel serving
TypeModels & adaptersApps & systems
SubcategoryLanguage modelsAI apps
PlatformNot verifiedNot verified
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Check current official software, hosting, model and infrastructure pricing.
Pricing source——
First collected2026-11-032026-11-03
MetricRepository stars, not unique users or individual-skill installsRepository stars, not unique users or individual-skill installs
LanguagePythonHTML
About this projectTensorRT 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.This project aims to share the technical principles and practical experience related to large models (large model engineering, large model application implementation)
RepositoryNVIDIA / TensorRT-LLMliguodongiot / llm-action
Measured at2026-11-03 08:24 UTC2026-11-03 08:25 UTC

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