LiteRT

LiteRT

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About

The Apple Foundation Models framework lets developers perform tasks with Apple’s on-device model that specializes in language understanding, structured output, and tool calling. It provides access to the on-device large language model that powers Apple Intelligence, helping apps perform intelligent tasks specific to their use case. The text-based on-device model identifies patterns that allow it to generate new text appropriate for the request, and it can make decisions to call code written by the developer to perform specialized tasks. Developers can generate text content for a wide range of tasks, including summarization, entity extraction, text understanding, refinement, dialog for games, creative content generation, classification, and more. It also supports guided generation, allowing developers to generate entire Swift data structures with strong guarantees by using the Generable macro.

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

Apple app developers who need to add private, on-device generative AI features with structured output and tool calling

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

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

Apple
Founded: 1976
United States
developer.apple.com/documentation/FoundationModels

Company Information

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

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Categories

Categories

Integrations

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

Integrations

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