alt Hacker NewsConsider this. One of the smallest Qwen models (4B parameters) powers my home automation voice assistant, and runs on CPU alone at >20 tok/s. It is enough for that use case, and could be made even better/faster with a modest GPU. It isn't as smart as some cloud-connected thingamajig, but I would never allow a literal Google or Amazon bug in my home. Huge SOTA models aren't relevant everywhere. Most people use LLMs for rather trivial tasks such as finding typos or drafting text.
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dainiusse • today at 6:25 AM
Curious, what exactly does it do for you? I has bad luck with these small models to do anything useful tbh.
But with Apple's AFM 3 architecture, we might end up with huge SOTA adjacent on devices with limited RAM.
They use a technique where you only load between 1B and 4B of a 20B dense model for an entire prompt run, not token by token like a MoE, and use mostly the low power ANE instead of GPU cores.
Now, imagine if/when they scale up to 100B or more? On a chip using 2W?