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Agreed, seems like the M5 has already made steps in that direction, with 4x prompt processing / prefill performance vs. M4. [1] And token generation also got a 10% boost. The data below is only for Pro & Max but I think the base M5 got the same relative boosts vs. M4 base.

    Chip         BW (GB/s)   GPU Cores   Q4_0 Prompt   Q4_0 Gen
    M4 Pro (20c)    273         20          439.78        50.74
    M4 Max (40c)    546         40          885.68        83.06
    M5 Pro (20c)    307         20      ~1500 to 1700    ~56
    M5 Max (40c)    614         40      ~3000 to 3500    ~92
[1] https://www.hardware-corner.net/m5-pro-m5-max-local-llm-4x-f...
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ELI5?
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Look at the "Q4_0 Prompt" column. That's the tokens-per-second processing the initial prompt/system prompt. This is where the "neural accelerators inside each GPU core" is seen most prominently.
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The M5 GPU added better matmul and dot product support in hardware (IIRC) that really boosted performance of those kernels over previous GPUs. Current transformer models rely heavily on matmuls. Prefill (processing the current context) is mostly limited by raw GPU processing power where token generation (predicting the next token from the current context) is mostly limited by memory bandwidth.

While an older M-series might run a matmul or dot product kernel just fine the M5 can run them much faster.

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  Apple's biggest bottleneck for real-world inference is prefill processing.
Much less true since the M5 generation. Prefill, aka prompt processing, got a 4x increase.
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