Project Title

TensorRT-LLM — Optimized Large Language Model Inference on NVIDIA GPUs

Overview

TensorRT-LLM is an open-source project that offers a Python API for defining and optimizing Large Language Models (LLMs) for efficient inference on NVIDIA GPUs. It stands out for its state-of-the-art optimizations and support for creating both Python and C++ runtimes, ensuring high-performance execution of inference tasks.

Key Features

Easy-to-use Python API for defining LLMs
State-of-the-art optimizations for inference efficiency
Support for Python and C++ runtimes
Comprehensive documentation and examples

Use Cases

Researchers and developers using LLMs for natural language processing tasks
Enterprises requiring high-performance inference on NVIDIA GPUs
Academic institutions for teaching and research in AI and machine learning

Advantages

Enhanced inference performance through optimizations tailored for NVIDIA GPUs
Flexibility in runtime development with support for both Python and C++
Day-0 support for the latest open-weights models, ensuring users can leverage the most recent advancements immediately

Limitations / Considerations

The project is specifically designed for NVIDIA GPUs, which may limit its applicability in environments without such hardware
Users need to be familiar with both Python and C++ for full utilization of the project's capabilities

Hugging Face Transformers: A library of pre-trained models for Natural Language Processing, differing in its broader scope beyond just inference optimization.
NVIDIA TensorRT: A C++ library for optimizing and deploying deep learning models, which TensorRT-LLM builds upon for LLM-specific optimizations.

Basic Information

GitHub: TensorRT-LLM
Stars: 11,647
License: Apache 2.0
Last Commit: 2025-09-23

📊 Project Information

Project Name: TensorRT-LLM
GitHub URL: https://github.com/NVIDIA/TensorRT-LLM
Programming Language: C++
⭐ Stars: 11,647
🍴 Forks: 1,754
📅 Created: 2023-08-16
🔄 Last Updated: 2025-09-23

🏷️ Project Topics

Topics: [, ", b, l, a, c, k, w, e, l, l, ", ,, , ", c, u, d, a, ", ,, , ", l, l, m, -, s, e, r, v, i, n, g, ", ,, , ", m, o, e, ", ,, , ", p, y, t, o, r, c, h, ", ]