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OrcaRouter’s analysis of Liquid AI’s speculative-decoding draft reports an average 2.54× speed-up on an H100, but only 1.18× on an M4 Max MacBook Pro. The trick can make an AI model produce tokens faster without changing its output, but the gains depend sharply on the hardware.
Why it mattersThe figures are Liquid’s reported benchmarks, not independent tests. For anyone hoping to run models locally, the useful lesson is that a headline speed-up on a data-centre GPU may tell you rather little about your laptop.
Discuss: When judging local AI tools, should developers prioritise laptop results over headline speed-ups on data-centre hardware?
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