sleepyeldrazi

5 ms·

1. 31.▲
   by sleepyeldrazi 6mo ago

   I haven't honestly dug around to figure out if there's a hardware reason for it, but prompt processing has always been a lot slower for me on macs in general. I mostly use MLX on my 24GB M4 Pro though, so I will pull llama.cpp on
2. 32.▲
   by sleepyeldrazi 6mo ago

   I have been testing and using Qwen3.6 27B (running from my 3090) since it dropped and I genuinely think this is the first consumer hardware-grade model that can actually replace frontiers for a lot of workloads. I ran 8 tests on a variety o
3. 33.▲
   by sleepyeldrazi 6mo ago

   I have been getting good results with IQ4_NL and TurboQuant at 4bits on 24gb (3090). It easily fits 256k with that setup, but it starts slowing down quite a bit after 80-100k. Quality in my testing is also still good: - Coding task test: h
4. 34.▲
   by sleepyeldrazi 6mo ago

   I ran 3 prompts (short versions, full version in the repo): - Implement a numerically stable backward pass for layer normalization from scratch in NumPy. - Design and implement a high-performance fused softmax + top-k kernel in CUDA (or CUD
5. 35.▲
   The only non-LLM-generated file in my repo(github.com)

   2 points by sleepyeldrazi 6mo ago|1 comments
6. 36.▲
   by sleepyeldrazi 5y ago

   If he can comfortably move his head, might I suggest something VR related? Most of the first VR games that came out for mobile (i.e. using your phone as a VR screen) couldn't utilise a controller so they used head movement for controll