If you do good work you should at least take the time to review the slop that details that work for slopiness. Otherwise it's hard to take it seriously. Especially the prefill section.
This part sounds like AI assisted setting this up and benchmarking it:
>The fix was trivially simple: zero-pad the head count 12→16, run the fast kernel, and extract the real 12 heads from the output.
I've recently used a frontier AI (ChatGPT 5.6 Sol on ultra) to set up a much smaller local model, and the performance optimizations it introduced left the model totally incoherent. (The model just repeats a single character, etc.)
When I see a line like the one I just quoted, it leaves me wondering if the setup is still coherent like a stock install of Kimi K3 on supported hardware.
Did they run any benchmarks on it to see if it is still correct?
>The fix was trivially simple: zero-pad the head count 12→16, run the fast kernel, and extract the real 12 heads from the output.
I've recently used a frontier AI (ChatGPT 5.6 Sol on ultra) to set up a much smaller local model, and the performance optimizations it introduced left the model totally incoherent. (The model just repeats a single character, etc.)
When I see a line like the one I just quoted, it leaves me wondering if the setup is still coherent like a stock install of Kimi K3 on supported hardware.
Did they run any benchmarks on it to see if it is still correct?