Hi, We are a small research lab in North sweden and today we want to share another "optimal setup" that are researching. Research was done using Claude, skyclaw (our own Sysops AI harness) Our hopes is that by sharing this - others will be able to run great models at home and that we will get some good suggestions for improving. So.. a bit of stats.. Prompt Fast profile (NVFP4, live) Max-context profile (QAT Q4) Start (abliterated Q4_K) 2K 3,067 1,427 1,335 8K 4,154 1,531 1,409 32K 3,438 1,332 1,272 (24K) 64K 2,579 1,092 — ~130K ~1,600 ~710 (before FP8 attention) — ~185K / ~231K — 613 / 528 — Decode. One user, MTP with 7 drafts (greedy / sampled tok/s): Workload Fast profile (live) Max-context profile Start Short chat, 10 prompts × 512 tokens 118.4 / 114.0 106.8 / 99.7 33.2 After 2K of context 107.3 / 119.6 93.2 / 110.0 32.6 After 8K of context 110.3 / 118.9 106.2 / 104.7 32.3 Any feedback or recomendations are welcome: https://github.com/inordic/rtx5090-NInferno-gemma4-31b   submitted by   /u/leonbollerup [link]   [comments]