Comment by reinitctxoffset

2 days ago

I'm dusting off the local models thing after being too busy for a while and it is crazy how wrong the benchmarks and general narrative is.

First, vLLM is like, we can do better than this, we need a better default target. It parses capability wrong, silently falls back on sm_80 xmma kernels when cutlass3x_sm120_bstensorprop_... CASK kernels are available, has mad Python in the hot path, emits dubious tool call syntax, and just managed to do something so off-road it tripped a driver bug that managed to wedge MMIO so bad the EC couldn't get an SBR out so the fan was going literally max until I hard pulled power. They say AMD is worse and I'll take their word for it because patching the driver and Inductor both in the same day is plenty of grief for me.

But the amazing thing and why your comment prompted me to write all this is that Qwen3.6 is insanely good, so good I am seriously questioning the MoE dogma. I was running the NVFP4 quant with the BF16 drafter, 100+ tokens a second of clean, legible reasoning trace and flawless tool calls. It's small and you can tell it hasn't memorized half the internet, but it's reasoning is like, better than most frontier. Opus has cleaner reasoning, GPT 5.x and Gemini 3.x Pro do not. If someone scaled that boi up by 5x? I get the feeling DeepSeek did so many arch innovations in one release that they just didn't quite have the convergence, this is like, the fundamentals as artistry. It's wayyyyyy stronger than GPT-4o at over a trillion parameters.

The other thing is I was using it on OpenRouter and it was all janky in the traces, stuttering and going in circles. On another day I would have been like "what do you expect it's the size of an iPhone". I wonder how many other people have drawn that conclusion too.

I'm not going to call it a conspiracy because it's explained by neglect, but we haven't even scratched the surface of the local model ceiling. With a harness that kept the data fresh, scale up the parameter count a bit, stretch context out a bit, and write an LLM serving engine that isn't hobbyist Python jank wrapped around fuckin inductor/triton jank?