Morning Edition · Tuesday, August 4, 2026Published at 2:16 AM EDT · New York
An Open-Source Runtime Streams Mixture-of-Experts Weights From SSD to Run an 80-Billion-Parameter Qwen on a Mac
Swiftlet keeps only the dense core in memory and fetches each routed expert with a single disk read, putting a 35-billion-parameter model on an iPhone at roughly one token per second.
A Swift and Metal runtime called Swiftlet applies a straightforward observation about sparse models to deployment. In a mixture-of-experts (MoE) model, only a small fraction of parameters activate per token, so the routed experts do not nee…
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Part of a tracked trend
AI Inference Shifts to Consumer Devices
Over the next 3-6 months, smaller efficient architectures and inference-cost optimizations push capable AI off the cloud and onto laptops, phones, and mobile NPUs.
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