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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.

About

ZeroGPU is a compute efficiency layer for AI inference that helps AI applications reduce inference costs by moving high-volume tasks to specialized models across an edge-powered inference network. It is built around the idea that most production AI workloads do not need frontier-scale reasoning; tasks such as document analysis, content summarization, page classification, signal extraction, PII detection, web content processing, query routing, and message moderation can often run on smaller, task-specific models instead of expensive frontier models. ZeroGPU helps developers identify workloads that do not require deep reasoning, route them to specialized small language models and nano models, execute them across optimized servers, approved edge capacity, and cloud fallback, then measure cost reduction, latency improvement, avoided frontier-model calls, and model performance.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

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

Audience

AI application developers, platform teams, and infrastructure engineers who need to offload high-volume inference tasks to specialized models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

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

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

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

ZeroGPU
Founded: 2025
United States
zerogpu.ai/

Alternatives

OpenVINO

OpenVINO

Intel

Alternatives

Categories

Categories

Integrations

CUDA
Dataoorts GPU Cloud
Kimi K2
Kimi K2.5
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Broadcast
NVIDIA DRIVE
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA virtual GPU
OpenAI
PyTorch
Python
RankGPT
TensorFlow
Ultralytics

Integrations

CUDA
Dataoorts GPU Cloud
Kimi K2
Kimi K2.5
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Broadcast
NVIDIA DRIVE
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA virtual GPU
OpenAI
PyTorch
Python
RankGPT
TensorFlow
Ultralytics
Claim NVIDIA TensorRT and update features and information
Claim NVIDIA TensorRT and update features and information
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