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About

ExecuTorch is PyTorch’s open source framework for deploying AI/ML models directly to edge devices, enabling text, vision, speech, recommendation, and multimodal inference without requiring the cloud. It exports models from PyTorch without intermediate conversion formats, preserves ATen operators, and uses ahead-of-time compilation to optimize performance for target hardware before deployment. Its modular design lets developers choose compile-time and runtime optimizations while staying inside the familiar PyTorch ecosystem, including torchao for quantization. A portable C++ runtime with a base footprint of about 50 KB can run on smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. ExecuTorch supports Android, iOS, Linux, Windows, macOS, and WebAssembly, with native APIs for C++, Swift, Kotlin, and Objective-C.

About

Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers and engineering teams that need to deploy optimized PyTorch models for on-device inference across smartphones, embedded systems, and microcontrollers

Audience

Machine learning practitioners and researchers in search of a tool to implement privacy-preserving, decentralized model training across diverse devices and platforms

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Supported

Company Information

ExecuTorch
United States
executorch.ai/

Company Information

Flower
Founded: 2023
Germany
flower.ai/

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

Keepsake

Keepsake

Replicate
LiteRT

LiteRT

Google

Categories

AI Inference Supported

Categories

Integrations

PyTorch Supported
Amazon Web Services (AWS) Not Supported
Android Not Supported
Apple iOS Not Supported
Facebook Supported
Hardskills Not Supported
JAX Not Supported
Kotlin Supported
LLaVA Supported
Llama 3.2 Supported
MXNet Not Supported
Microsoft Azure Not Supported
Muse Glimmer Supported
NVIDIA Jetson Not Supported
Objective-C Supported
Phi-4-mini-reasoning Supported
Qwen3 Supported
Raspberry Pi OS Not Supported
Swift Supported
pandas Not Supported

Integrations

PyTorch Supported
Amazon Web Services (AWS) Supported
Android Supported
Apple iOS Supported
Facebook Not Supported
Hardskills Supported
JAX Supported
Kotlin Not Supported
LLaVA Not Supported
Llama 3.2 Not Supported
MXNet Supported
Microsoft Azure Supported
Muse Glimmer Not Supported
NVIDIA Jetson Supported
Objective-C Not Supported
Phi-4-mini-reasoning Not Supported
Qwen3 Not Supported
Raspberry Pi OS Supported
Swift Not Supported
pandas Supported
Claim ExecuTorch and update features and information
Claim ExecuTorch and update features and information
Claim Flower and update features and information
Claim Flower and update features and information