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Re:Show HN: We made our own inference engine for Apple Silicon by AlekseiSavin on Tuesday July 15, 2025 @11:57AM (#44572508)
You're right, modern edge devices are powerful enough to run small models, so the real bottleneck for a forward pass is usually memory bandwidth, which defines the upper theoretical limit for inference speed. Right now, we've figured out how to run computations in a granular way on specific processing units, but we expect the real benefits to come later when we add support for VLMs and advanced speculative decoding, where you process more than one token at a time
Re:Show HN: We made our own inference engine for Apple Silicon by J_Shelby_J on Tuesday July 15, 2025 @12:34PM (#44572973)
VLMs = very large models?
Re:Show HN: We made our own inference engine for Apple Silicon by mmorse1217 on Tuesday July 15, 2025 @12:39PM (#44573059)
Probably vision language models.