LiteRT

LiteRT

Google
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About

LiteRT (Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. It enables developers to deploy machine learning models across various platforms and microcontrollers. LiteRT supports models from TensorFlow, PyTorch, and JAX, converting them into the efficient FlatBuffers format (.tflite) for optimized on-device inference. Key features include low latency, enhanced privacy by processing data locally, reduced model and binary sizes, and efficient power consumption. The runtime offers SDKs in multiple languages such as Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating integration into diverse applications. Hardware acceleration is achieved through delegates like GPU and iOS Core ML, improving performance on supported devices. LiteRT Next, currently in alpha, introduces a new set of APIs that streamline on-device hardware acceleration.

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.

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

Mobile application developers in search of a tool to integrate efficient, on-device AI capabilities into their apps

Audience

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

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

Free
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

Google
Founded: 1998
United States
ai.google.dev/edge/litert

Company Information

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

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

OpenVINO

OpenVINO

Intel

Categories

Categories

Integrations

PyTorch
Python
TensorFlow
C++
CUDA
Hugging Face
Java
Kimi K2
Kimi K2.5
LaunchX
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Morpheus
NVIDIA Riva Studio
NVIDIA virtual GPU
RankLLM
Rosepetal AI
Thunder Compute
Ultralytics

Integrations

PyTorch
Python
TensorFlow
C++
CUDA
Hugging Face
Java
Kimi K2
Kimi K2.5
LaunchX
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Morpheus
NVIDIA Riva Studio
NVIDIA virtual GPU
RankLLM
Rosepetal AI
Thunder Compute
Ultralytics
Claim LiteRT and update features and information
Claim LiteRT and update features and information
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Claim NVIDIA TensorRT and update features and information