whatmodel.sh / decision / Shisa DE-2 (repeat)
Shisa DE-2 (repeat)
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Shisa DE-2 (repeat) is an open-weights decision model from Shisa.AI. Its published size is 25.81B parameters. Licence: apache-2.0.
Catalogue identity notes
Exact Decision Index tested engine shisa-de-2-repeat; reported model Shisa DE-2 (repeat). 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.
$ how it compares
The decision models ranked either side of Shisa DE-2 (repeat), out of 357 with a score, then more from Shisa.AI.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 193 |  JEV-9B | 52±1 | model files | ||
| 194 |  Aplomb 1 | 52±1 | request access | ||
| 195 | Shisa DE-2 (repeat) | 51±4 | model files | ||
| 196 |  ZTC-Judge-9B (DecisionBench 05d154a5) | 51±2 | model files | ||
| 197 | Jev-Omni | 51±1 | model files | ||
| more from Shisa.AI | |||||
| 89 | Shisa DE-2.1 (repeat) | 62±1 | model files | ||
see all decision models · find the ones that fit your machine
$ what it's good at
vision▁·▃▂▃▃▇▄▄█▄▃ #60 of 79 · 95% of its score · 12 tests
Trails RSI-Jev v5.0 VL 3B, Valen-4B, InternLM Intern-Decision Qwen3.5-4B 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 | 60.6700 points ✎ | ▁·▁▁▃▁▄▄▃▅█▂ beats 13/61 | 12% |
| Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted | 29.1900 points ✎ | ▁▁▅▁▄▁▄█▄▃▇▇ beats 27/61 | 11% |
| Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted | 76.5000 points ✎ | ▁·▁▁▁▁·▂▁▃▅█ beats 20/61 | 10% |
| Decision Index Vision 0.4: private same skills (points) | 47.4400 points ✎ | ▁▁▃▃▁▃▄▆▃▃▅█ beats 16/61 | 10% |
| Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted | 38.8300 points ✎ | ▆▃▃▆▄▄▇██▁▆▆ beats 35/61 | 8.8% |
| Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted | 53.1100 points ✎ | ▁·▂▂▁▃▃▅▅▃▂█ beats 15/61 | 8.0% |
| Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted | 67.4200 points ✎ | ▂▁▁▁▁▃▁▅▅▆██ beats 22/61 | 7.8% |
| Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted | 90.1600 points ✎ | ▁·▁▂▁▁▃▁▃▂▅█ beats 26/61 | 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 | 29.7900 points ✎ | ▂▄▇▆█▄▄▇▂··▁ beats 40/61 | 6.2% |
| Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted | -6.0000 points ✎ | ▃···▁▂▂▂█▄▂▃ beats 0/61 | 5.9% |
| Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted | 68.5900 points ✎ | ▁▁▁▁▂▁▃▁▄█▃▃ beats 15/61 | 4.7% |
| Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted | 90.5800 points ✎ | ▁··▁▁▁▁▁▂▄█▁ beats 25/61 | 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/shisa-ai ↗
$ 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 | = 51.2 |
$ 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