WhatA developer SDK that enables any mobile app to run large language models locally on-device using SSD-to-GPU streaming and mixture-of-experts optimization.
SignalThe demonstration that a 400B parameter model can run on a consumer phone proves that the software optimization layer for on-device inference is the real bottleneck — not hardware — and whoever owns that middleware layer captures enormous value.
Why NowApple's LLM-in-a-Flash techniques combined with mixture-of-experts architectures have just proven viable on mobile silicon, but there's no turnkey SDK for third-party developers to leverage this.
MarketMobile app developers building AI features; TAM tied to the $200B+ mobile app economy. Competitors include Apple's own CoreML (limited to Apple ecosystem), ONNX Runtime, and llama.cpp, but none offer optimized MoE streaming for mobile.
MoatDeep hardware-specific optimization knowledge and model-device compatibility testing creates high switching costs once developers integrate the SDK.
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