LiteRT

LiteRT

Google
+
+

Related Products

  • Google Compute Engine
    1,168 Ratings
    Visit Website
  • RunPod
    206 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    961 Ratings
    Visit Website
  • Google Cloud Platform
    60,933 Ratings
    Visit Website
  • Teradata VantageCloud
    1,107 Ratings
    Visit Website
  • DataBuck
    6 Ratings
    Visit Website
  • OpenMetal
    39 Ratings
    Visit Website
  • Nasdaq Metrio
    14 Ratings
    Visit Website
  • RunMyJobs by Redwood
    425 Ratings
    Visit Website
  • PackageX OCR Scanning
    46 Ratings
    Visit Website

About

Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.

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.

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

Companies interested in a GPU server solution for AI and machine learning

Audience

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

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

$1 per hour
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

GPUonCLOUD
India
gpuoncloud.com/gpu-as-a-service/

Company Information

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

Alternatives

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

PyTorch
TensorFlow
C++
Google AI Edge Gallery
JAX
Java
Kotlin
MXNet
Objective-C
Python
Swift

Integrations

PyTorch
TensorFlow
C++
Google AI Edge Gallery
JAX
Java
Kotlin
MXNet
Objective-C
Python
Swift
Claim GPUonCLOUD and update features and information
Claim GPUonCLOUD and update features and information
Claim LiteRT and update features and information
Claim LiteRT and update features and information