whatmodel.sh / decision / OneJev1.5-9B
OneJev1.5-9B
↗ share
+ contribute
OneJev1.5-9B is an open-weights decision model from OmniJev, released 13 October 2026. Its published size is 9.41B parameters. Licence: apache-2.0.
Catalogue identity notes
Exact Decision Index tested engine onejev1.5-9b; reported model OneJev1.5-9B. Type: full fine-tune; technique: autoregressive. Comparison entry; no current run command, API price or speed inferred from the benchmark. Current repository metadata checked separately; an unpinned alias is not evidence that today’s weights reproduce this historical run.
Model information sources
Release date ↗ · Weights licence ↗ · Parameter count ↗
Publisher parameter count; includes the served backbone, not just adapter size.
$ how it compares
The decision models ranked either side of OneJev1.5-9B, out of 357 with a score, then more from OmniJev.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 105 | reflex-qwen3.5-4b-lora (DecisionBench 9df1cbbb) | 61±2 | model files | ||
| 106 | reflex Qwen3.8-27B-FP8 (pmscr) (decision readout) | 61±1 | source code | ||
| 107 | OneJev1.5-9B | 61±4 | model files | ||
| 108 |  imajev-4b (DecisionBench c9e5f132) | 61±2 | model files | ||
| 109 | AJev lora1 (Gemma 4 26B-A4B) | 60±1 | model files | ||
| more from OmniJev | |||||
| 23 | OneJev1.6-27B | 69±2 | model files | ||
| 58 | OneJev1.5-27B | 65±4 | model files | ||
| 68 | OneJev1.6-9B | 64±1 | model files | ||
see all decision models · find the ones that fit your machine
$ what it's good at
vision▁·▃▂▃▃▇▄▄█▄▃ #36 of 79 · 95% of its score · 12 tests
Beats RSI-Jev v6.1 VL 27B (effort auto), StartLux-Decision v1.1 4B, Surogate Rune 26B-A4B v3 here, though they rank higher overall. Trails Clef-flash, Xor 1.2 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted | 77.3900 points ✎ | ▁·▁▁▃▁▄▄▃▅█▂ beats 33/61 | 12% |
| Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted | 33.5700 points ✎ | ▁▁▅▁▄▁▄█▄▃▇▇ beats 36/61 | 11% |
| Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted | 77.7500 points ✎ | ▁·▁▁▁▁·▂▁▃▅█ beats 26/61 | 10% |
| Decision Index Vision 0.4: private same skills (points) | 54.9500 points ✎ | ▁▁▃▃▁▂▄▆▃▃▅█ beats 30/61 | 10% |
| Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted | 53.8300 points ✎ | ▆▃▃▆▄▄▇██▁▆▆ beats 55/61 | 8.8% |
| Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted | 63.6500 points ✎ | ▁·▂▂▁▃▃▅▅▃▂█ beats 38/61 | 8.0% |
| Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted | 75.4400 points ✎ | ▂▁▁▁▁▃▁▅▅▆██ beats 38/61 | 7.8% |
| Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted | 93.9900 points ✎ | ▁·▁▂▁▁▃▁▂▂▅█ beats 34/61 | 6.2% |
4 more tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted | 16.6200 points ✎ | ▂▄▇▆█▄▄▇▂··▁ beats 16/61 | 6.2% |
| Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted | 72.2900 points ✎ | ▁···▁▂▂▂█▄▂▃ beats 55/61 | 5.9% |
| Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted | 76.2800 points ✎ | ▁▁▁▁▂▁▁▁▄█▃▃ beats 41/61 | 4.7% |
| Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted | 92.9200 points ✎ | ▁··▁▁▁▁▁▂▄█▁ beats 55/61 | 3.4% |
$ where to run it
Download model files ↗
Published model files verified. This is a verified repository snapshot; the benchmark does not establish an identical weight revision. A local run command and hardware requirements have not been verified for this entry. Source · checked 2026-10-31.
Model repository and documentation: huggingface.co/OmniJev ↗
$ how the score was worked out · Decision Index Vision 0.4 95%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 Decision Index Vision 0.4 · submitted; independent execution unverified | 12 | 95% |
| prior · pull toward the middle | 5% | |
| weighted average | = 60.5 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json