Audience

Machine learning engineers and data scientists seeking a tool to optimize their deep learning operations

About NVIDIA TensorRT

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.

Pricing

Starting Price:
Free
Free Version:
Free Version available.

Integrations

API:
Yes, NVIDIA TensorRT offers API access

Ratings/Reviews

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Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/tensorrt

Videos and Screen Captures

NVIDIA TensorRT Screenshot 1
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Product Details

Platforms Supported
Cloud
Windows
Training
Documentation
Webinars
In Person
Videos
Support
Phone Support
Online

NVIDIA TensorRT Frequently Asked Questions

Q: What kinds of users and organization types does NVIDIA TensorRT work with?
Q: What languages does NVIDIA TensorRT support in their product?
Q: What kind of support options does NVIDIA TensorRT offer?
Q: What other applications or services does NVIDIA TensorRT integrate with?
Q: Does NVIDIA TensorRT have an API?
Q: What type of training does NVIDIA TensorRT provide?
Q: How much does NVIDIA TensorRT cost?

NVIDIA TensorRT Product Features