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OneJev1.5-0.8B
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OneJev1.5-0.8B is an open-weights decision model from OmniJev, released 13 October 2026. Its published size is 1.11B parameters. Licence: apache-2.0.
Catalogue identity notes
Exact Decision Index tested engine onejev1.5-0.8b; reported model OneJev1.5-0.8B. 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 OneJev1.5-0.8B, out of 357 with a score, then more from OmniJev.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 253 | Crivo-1B | 43±1 | model files | ||
| 254 |  vLLM-SR d3-lite (0.8B) | 42±1 | local | ||
| 255 | OneJev1.5-0.8B | 42±4 | model files | ||
| 256 | jevhome-ettin-1b (JevBench mini) | 42±2 | source code | ||
| 257 | vLLM-SR vela3-fast (Vela 3.0, 0.4B) | 42±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▁·▃▃▃▃▇▄▄█▄▃ #72 of 79 · 95% of its score · 12 tests
Beats Winnow-E4B, vLLM-SR d3-lite (0.8B) here, though they rank higher overall. Trails LiquidAI d1-omni-600M, InternLM Intern-Decision Qwen3.5-2B, Valen-2B 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 | 46.4200 points ✎ | ▁·▁▁▃▁▄▄▃▅█▂ beats 4/61 | 12% |
| Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted | 8.8400 points ✎ | ▁▁▅▁▄▁▄█▄▃▇▇ beats 8/61 | 11% |
| Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted | 55.0000 points ✎ | ▁·▁▁▁▃·▂▁▃▅█ beats 10/61 | 10% |
| Decision Index Vision 0.4: private same skills (points) | 36.8600 points ✎ | ▁▁▃▃▁▂▄▆▃▃▅█ beats 5/61 | 10% |
| Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted | 24.6500 points ✎ | ▆▃▃▆▄▄▇██▁▆▆ beats 16/61 | 8.8% |
| Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted | 41.4600 points ✎ | ▁·▂▃▁▃▃▅▅▃▂█ beats 6/61 | 8.0% |
| Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted | 57.3900 points ✎ | ▂▁▁▁▁▃▁▅▅▆██ beats 11/61 | 7.8% |
| Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted | 77.6000 points ✎ | ▁·▁▂▃▁▃▁▂▂▅█ beats 10/61 | 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 | 10.1200 points ✎ | ▂▄▇▆█▄▄▇▂··▁ beats 3/61 | 6.2% |
| Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted | 53.7700 points ✎ | ▁···▁▂▂▂█▄▂▃ beats 31/61 | 5.9% |
| Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted | 62.6800 points ✎ | ▁▁▁▁▃▁▁▁▄█▃▃ beats 9/61 | 4.7% |
| Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted | 83.8400 points ✎ | ▁··▁▁▁▁▃▂▄█▁ beats 7/61 | 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 | = 42.4 |
$ 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