MacBook vs. Dedicated GPU for LLM Inference: Unified Memory Trade-Offs
By
mzubairtahir
Summary
A brief Hacker News comment comparing MacBooks (with unified memory) to dedicated GPUs for running LLMs. The author notes MacBooks can run larger models slowly due to high unified memory, while dedicated GPUs run smaller models faster due to limited VRAM.
Source
Hacker NewsMacBook vs. Dedicated GPU for LLM Inference: Unified Memory Trade-Offsnews.ycombinator.comKey quotes
· 3 pulledMacBooks with their unified memory behave like a slow GPU with enormous amount of video RAM.
So you can run large smart models slowly.
Dedicated GPUs have less video RAM so can run smaller less smart models quickly.
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