whatmodel.sh / decision / jev-vision-27b

jev-vision-27b is an open-weights decision model from e12ex2. Its published size is 27.78B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine jev-vision-27b-r2; reported model jev-vision-27b. Type: LoRA; 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

· Weights licence ↗ · Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

63.5±3.5#71 of 355 decision modelsfrom 12 benchmark results across 1 source

$ how it compares

The decision models ranked either side of jev-vision-27b, out of 357 with a score.

#modelscorewhereRAMreleased
69JEV-27B-VL AutoTrust AI Lab64±4model files
70KnowLine 35B-A3B Gen1 PelaAI64±4model files2026-10-12
71jev-vision-27b e12ex264±4model files
72Xor 26B-A4B v1.2 Juspay Technologies63±1model files2026-10-16
73Senova-4B v2 WangSenQWQ63±1model files

see all decision models · find the ones that fit your machine

$ what it's good at

vision▁·▃▂▃▃▇▄▄█▄▃ #29 of 79 · 95% of its score · 12 tests

Beats StartLux-Decision v1.1 9B, RSI-Jev v6.1 VL 27B (effort auto), StartLux-Decision v1.1 4B here, though they rank higher overall. Trails Clef-flash, Perplexity Decider Flash v1.2 (4B), Mercury Decide (free endpoint) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted84.1000 points ✎▁·▁▁▃▁▄▄▃▅█▂ beats 49/61avg 63.423 points▇▇▇▇▇ 12%blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted38.0100 points ✎▁▁▅▁▄▁▄█▄▃▇▇ beats 39/61avg 22.797 points▇▇▇▇ 11%blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted83.5000 points ✎▁·▁▁▁▁·▂▁▃▅█ beats 41/61avg 66.987 points▇▇▇▇ 10%blunt
Decision Index Vision 0.4: private same skills (points)64.3200 points ✎▁▁▃▃▁▂▄▆▃▃▅█ beats 45/61avg 48.067 points▇▇▇▇ 10%blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted52.5100 points ✎▆▃▃▆▄▄▇██▁▆▆ beats 53/61avg 28.443 points▇▇▇▇ 8.8%blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted72.8100 points ✎▁·▂▂▁▃▃▅▅▃▂█ beats 51/61avg 53.651 points▇▇▇ 8.0%blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted78.7000 points ✎▂▁▁▁▁▃▁▅▅▆██ beats 44/61avg 62.137 points▇▇▇ 7.8%blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted97.2700 points ✎▁·▁▂▁▁▃▁▂▂▅█ beats 47/61avg 83.859 points▇▇ 6.2%blunt
4 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted24.3800 points ✎▂▄▇▆█▄▄▇▂··▁ beats 32/61avg 19.676 points▇▇ 6.2%blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted53.9300 points ✎▁···▁▂▂▂█▄▂▃ beats 35/61avg 44.994 points▇▇ 5.9%blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted76.7700 points ✎▁▁▁▁▂▁▁▁▄█▃▃ beats 46/61avg 67.662 points▇▇ 4.7%blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted91.1800 points ✎▁··▁▁▁▁▁▂▄█▁ beats 29/61avg 85.184 points▇ 3.4%blunt

$ where to run it

Download model files ↗
Published model files verified. Includes adapters or readout weights; follow the model documentation for the required base model. 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/e12ex2 ↗

$ 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

sourceresultsshare of the scorelicence
Decision Index Vision 0.4 · submitted; independent execution unverified12CC BY 4.0
prior · pull toward the middle
weighted average= 63.5

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