“litert-lm”
Function Calling and Structured Output for On-Device Agents with Gemma 4
Make on-device agents reliable with Gemma 4 function calling and constrained decoding. Learn structured output patterns, parse-error fallbacks, and how to build a trustworthy tool-calling loop with LiteRT-LM.
On-Device AI in the Browser: LiteRT-LM with WebGPU and WebAssembly
Run Gemma 4 LLM inference in the browser with LiteRT-LM, WebGPU, and WebAssembly. Learn the JavaScript API, serverless architecture, and how to build privacy-preserving web apps with zero backend.
Mastering Edge AI on Raspberry Pi with LiteRT and Gemma
Deploy Gemma and LiteRT on Raspberry Pi 5 to build autonomous robots and local AI agents. Learn CPU and GPU inference, the Reachy Mini dual-processing pipeline, and the litert-lm CLI workflow.
Running Gemma 4 On-Device in a Multi-Agent Flutter App
Lessons learned running Gemma 4 E4B inside a Flutter app with multi-agent concurrency. Learn the platform channel bridge pattern, engine singleton design, serialization, and the multimodal constraints that bite in production.
Building a High-Performance On-Device LLM Client in Flutter with Qualcomm QNN
Learn how to build a production-quality on-device LLM client in Flutter that runs Gemma 4 on Qualcomm NPUs. Covers Dart FFI vs MediaPipe delegates, model delivery workflows, self-healing registries, and streaming reasoning UX.
Blazing Fast On-Device GenAI with LiteRT-LM
A deep dive into the LiteRT-LM runtime powering on-device GenAI. Learn how multi-token prediction, memory-mapped embeddings, session management, and constrained decoding deliver blazing-fast Gemma 4 inference on mobile.
Bringing Agentic Skills to the Edge with Gemma 4
Learn how to give on-device apps true agentic capabilities with Gemma 4, LiteRT-LM, and Agent Skills. Build multi-step autonomous workflows that plan, call tools, and act entirely on the device.
The Future of Mobile Dev: On-Device Agents and Edge AI
Explore how on-device agents and edge AI are reshaping mobile development with Gemma 4, LiteRT-LM, and Flutter. Learn the architecture, tradeoffs, and code patterns for building privacy-first agentic apps that run entirely on the device.