A 125B model can now run on one gaming GPU
The real change is not the 100 tokens per second claim. A large model now runs on hardware many developers own.
But the headline has a catch.
A tool called Strata runs Qwen3.8-Flash-Next at home. The model has 125B parameters and it is open-weight (huggingface.co/Qwen/Qwen3.8-Flash-Next).
The HN title says "RTX 4090 at 100 tokens per second". The project docs do not measure a 4090. They report 94 tokens per second on a 12GB RTX 5070 with 64GB of RAM, and an estimate for the RTX 3090 (braindetox.kr/en/posts/qwen38_flash_next_125b_local_inference_2026.html).
My read: the real change is not the 100 number. A large model now runs on hardware many developers own.
Your pick: if you have a 12GB+ GPU and 64GB of RAM, try it on one real task this week. Do not trust the speed claim until you measure it.
12 months: local 100B-class models become normal for dev tools.
24 months: private coding agents run on laptops.
36 months: cloud APIs keep only the hardest jobs.
I could be wrong. The numbers are self-reported and nobody has reproduced them. RAM and SSD speed may decide your result.
What would you run locally if cost were zero?