google-ai-edge/LiteRT

Health v2 · maintenance only

Adoption not part of the score

3339 stars · 434 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LiteRT is Google's successor to TensorFlow Lite, an on-device runtime for high-performance ML and GenAI inference on edge platforms. It provides model conversion, CPU/GPU/NPU acceleration, and optimization tooling for deploying models on Android, iOS, embedded, and web targets.

Use cases

• run machine learning models on android devices
• deploy llm inference on mobile phones
• accelerate on-device inference with gpu and npu
• convert tensorflow models for edge deployment
• run ml models in the browser with webgpu
• deploy genai models on embedded hardware

When to choose

• you need fast on-device ML inference on Android, iOS, or embedded platforms
• you want to run LLMs or GenAI models locally without a server
• you need hardware acceleration across CPU, GPU, and NPU from one runtime
• you are migrating an existing TensorFlow Lite deployment

When to avoid

• you need server-side or cloud GPU training rather than edge inference
• you need a full training framework rather than a deployment runtime
• your target platform lacks LiteRT delegate support for your accelerator

Facets

framework · maturity active

machine-learning llm-inference gpu-computing sdk cli machine-learning deep-learning large-language-models mobile-development embedded-systems developer-tools windows cpp python wasm cross-platform embedded tensorflow-lite on-device-ai edge-ai inference-runtime genai npu-acceleration model-conversion android ios linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-ai-edge/LiteRT")