TensorRT-LLM provides Python and C++ runtimes with optimizations for language model inference on NVIDIA GPUs.

github.com/NVIDIA/TensorRT-LLM
TensorRT-LLM homepage screenshot

About TensorRT-LLM

TensorRT-LLM is a repository of software for running inference on large language models (LLMs) on NVIDIA GPUs. It provides a Python API for defining LLMs and includes components for building Python and C++ runtimes that manage how inference runs.

The project describes its code as optimizing inference with specialized kernels for common operations, an efficient runtime, and a Python-based framework that users can customize and extend. Its overview also states that it supports Visual Gen models. The repository's blog posts discuss topics such as speculative decoding, disaggregated serving, and expert parallelism. The source describes the software as targeting NVIDIA GPUs.

Key features

  • Python API for defining large language models
  • Specialized kernels for common model operations
  • Python and C++ runtimes that orchestrate inference execution
  • Pythonic framework for customizing and extending the system
  • Support for Visual Gen models, according to the repository overview
  • Technical posts cover speculative decoding, disaggregated serving, and expert parallelism
Best for: Developers and engineers who run LLM inference on NVIDIA GPUs and want to customize the serving software.
Good for
  • Provides a Python API for defining LLMs
  • Includes Python and C++ runtimes for managing inference execution
  • Offers a framework that users can customize and extend
Watch out for
  • Targets NVIDIA GPUs; the source describes no support for other hardware

TensorRT-LLM at a glance

Type
Open-source project
Pricing
Not confirmed. Check the site
Open source
Not stated
Language
English
Last checked
Oct 6, 2026 · Online when checked
Listed
Oct 5, 2026

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TensorRT-LLM FAQ

What hardware does TensorRT-LLM target?
The source describes TensorRT-LLM as providing inference optimizations for language models on NVIDIA GPUs.
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