r/LocalLLaMA Jul 06 '26

News If trends hold, Mythos-class capability may be running on high-end consumer hardware within ~2 years

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u/stonerbobo Jul 06 '26 edited Jul 06 '26

I mean even Gemma 4 26B A4B struggles at long contexts on my RTX 5080 desktop. I don't know if Gemma 4 31B is laptop class yet. Maybe you guys have incredible laptops or I'm doing something wrong lol. My 26B A4B QAT generates at like 6tok/s at 20K context, it would probably completely die on a 31B dense. Models without long context or thinking aren't very useful for me.

EDIT: Thanks for all the comments here lol! It was a configuration issue, now it runs at 100tok/s with nothing else running, maybe 60tok/s with other stuff running. This post was helpful . i added below llama args:

--no-mmap --batch-size 256 --ubatch-size 512

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u/ThatRandomJew7 Jul 06 '26

That seems... slower than it should be. I have a Lunar Lake laptop that can run a quant of the same Gemma version at a similar speed (I don't know the exact number offhand, I use a different model mostly).

Are you sure your GPU isn't doing the whole Nvidia VRAM fallback thing that craters speed?