Seb-9B-v2: same size class, happy to compare on identical rows
Same size class, different recipe. Disclosure: I'm the author of Seb-9B-v2 (https://huggingface.co/ironbcc/Seb-9B-v2), a 9B decision model on Qwen3.5-9B, Apache-2.0. It returns a probability for every option in one forward pass, speaks /v1/systemone and a plain chat API, reads images, and takes inputs up to 32k tokens. These are self-run numbers, not independent ones: Decision Index 0.3 public index 59.16 (board numbers: Jev 1.13 57.96, Jev 1.14 60.70), ahead of Jev 1.13 on 22 of 37 benchmarks and clearly behind it on knowledge and reasoning. About 22 ms per decision on one RTX PRO 6000, about 88 ms on an Apple M5 Max. Write-up with the misses included: https://huggingface.co/blog/ironbcc/seb-9b-v2
If you're interested I can run a row-for-row comparison like the one I did for JEV-27B-VL.