Cloud-hosted LLMs and vision models have simplified AI integration, but they introduce heavy trade-offs: continuous API expenses, high latency over mobile networks, mandatory internet connectivity, and data privacy concerns.

Running inference directly on consumer client devices, utilizing client-side GPUs, NPUs, and CPU threads, solves these pain points. However, shipping on-device AI requires balancing hardware limitations, binary sizes, thermal throttling, and model quantization.

In this deep-dive joint session, two engineers will walk you through the practical reality of local inference across the two largest client frontiers: the Modern Web and Cross-Platform Mobile (Flutter).

What We’ll Cover:
1. Foundations of Local Inference
2. Local AI in the Browser with Transformers.js
3. On-Device AI on Mobile with Flutter & LiteRT-LM
4. Web vs. Mobile: Architectural Comparison & Hybrid Patterns