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LiteRT

On-device runtime for running ML and generative AI models on edge hardware

  • AI models and runtimes
View on GitHub
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What it is

LiteRT is Google's runtime for running machine learning models directly on phones, desktops, browsers, and embedded devices, continuing the TensorFlow Lite line. It handles converted PyTorch, TensorFlow, and JAX models, picks CPU, GPU, or NPU acceleration automatically, and works alongside companion projects for on-device LLMs and in-browser inference via WebGPU and WASM. Mobile and embedded developers use it to ship models inside their apps without calling a cloud service.

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Facts

Stars
3,506 GitHub stars.
3,506

Forks
476
Commits
6,890
Contributors
231
Language
C++
License
Apache-2.0
Last commit
Oct 20, 2026
On GitHub since
September 2024
First release
September 2024
Platforms
web, macOS, Windows, Linux, iOS, Android, library
Self-hostable
No
Alternative to
Core ML
Tags
  • machine-learning
  • llm-inference
  • embedded
  • local-ai
  • model-optimization
  • gpu-computing

Last synced from GitHub on Oct 20, 2026

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What people are saying

Updated Oct 21, 2026
  • Hacker NewsLiteRT – Google's Edge ML FrameworkJan 12, 2026 · 2 points · 0 comments (opens Hacker News in a new tab)