WhatA desktop app that automatically optimizes and splits large language models across GPU and system RAM, letting users run any model with a single click regardless of VRAM limitations.
SignalMultiple users express frustration at not having enough VRAM to run interesting models, and others point out that workarounds like CPU/GPU splitting exist but require technical setup — suggesting a gap between capability and usability for hobbyist and prosumer users.
Why NowOpen-weight models are proliferating rapidly, consumer GPU VRAM has stagnated at 16-24GB for most users, and quantization techniques have matured enough to make hybrid CPU/GPU inference practical.
MarketAI hobbyists, developers, and researchers running local models; ~5M+ users of llama.cpp/ollama/LM Studio today, growing fast. Competes with LM Studio and ollama but neither handles automatic hardware profiling and optimal layer splitting well.
MoatHardware profiling database and automatic optimization heuristics that improve with scale — the more hardware configs seen, the better the recommendations become.
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