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JEV Ettin 150M
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JEV Ettin 150M is an open-weights decision model from Elfsong, released 23 October 2026. Its published size is 0.15B parameters. Licence: apache-2.0.
Catalogue identity notes
Exact Decision Index tested engine jev-ettin-150m; reported model JEV Ettin 150M. Type: full fine-tune; technique: encoder. 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 JEV Ettin 150M, out of 357 with a score, then more from Elfsong.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 285 | 34±1 | model files | |||
| 286 | 34±1 | model files | |||
| 287 | JEV Ettin 150M | 34±1 | model files | ||
| 288 | 34±1 | model files | |||
| 289 | 33±1 | model files | |||
| more from Elfsong | |||||
| 299 | JEV FLAN-T5 Large public v2 (342M) | 32±1 | model files | ||
| 319 | JEV Ettin 400M | 29±1 | model files | ||
see all decision models · find the ones that fit your machine
$ what it's good at
tools & automation▁▃▁▁▁▃▃▄▆██▆ #211 of 250 · 10% of its score · 6 tests
Beats Cam1, InternLM Intern-Decision Qwen3.5-2B here, though they rank higher overall. Trails JevK5 Lite, Crivo-32M v2, Mola-68M here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: BFCL (case exact accuracy) submitted | 76.3% ✎ | ▁▂▁▁▁▃▂▄▅▆█▁ beats 38/246 | 5.4% |
| Decision Index 0.4.1: API-Bank (accuracy) submitted | 41.7% ✎ | ▁▁▁▁▁▁▁▃▃▂█▂ beats 34/236 | 2.2% |
| Decision Index 0.4.1: When2Call (accuracy) submitted | 69.4% ✎ | ▁▁▁▂▃▅▅▆█▇█▃ beats 94/246 | 1.1% |
| Decision Index 0.4.1: ToolRet (nDCG@10) submitted | 61.0% ✎ | ▁▁▁▁▁·▁▁▁▄█▁ beats 73/246 | 0.7% |
| Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted | 81.8% ✎ | █▁▁▃▄▄▆▄▁▂▁▃ beats 199/243 | 0.3% |
| Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted | 67.3% ✎ | no other model yet | — |
retrieval & classification▁▁▁·▁▁▁▁▃▃█▅ #178 of 258 · 4.7% of its score · 7 tests
Beats Solar Decide, JevK5 9B v0.3.3, Aplomb 1 here, though they rank higher overall. Trails Mola-68M, Bosun v3.1 1.7B LoRA, Dinah-1 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted | 43.8% ✎ | ▁▁▁▁▁▁▂▂▃▃█▅ beats 78/246 | 1.4% |
| Decision Index 0.4.1: BRIGHT (nDCG@10) submitted | 28.4% ✎ | ▁▁▁▁▁▁▁▃▂▄▇█ beats 41/246 | 1.4% |
| Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted | 92.5% ✎ | ▁▁▁▁▁▁▁▂▃▆█▄ beats 166/238 | 0.6% |
| Decision Index 0.4.1: HoVer (accuracy) submitted | 85.2% ✎ | ▆▆▇▅▄▄▃▇▄█▆▄ beats 187/246 | 0.5% |
| Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted | 50.1% ✎ | █▅▅▄▃▂▁▁▁▁·▁ beats 28/245 | 0.5% |
| Decision Index 0.4.1: BANKING77 (macro-F1) submitted | 91.8% ✎ | ▁·▁▁▁▁▁▁▂█▇█ beats 210/238 | 0.3% |
| Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted | 37.1% ✎ | no other model yet | — |
language understanding▂▂▂▃▂▅▆▃█▆▄▃ #206 of 256 · 24% of its score · 9 tests
Beats Valen-2B, Saina Helm 2 Omni (0.8B), vLLM-SR Decision 2.0 Sol 2B here, though they rank higher overall. Trails DecisionTune 1.0, vera-spark, JEV FLAN-T5 Large public v2 (342M) here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: HellaSwag (accuracy) submitted | 64.3% ✎ | ▂▄▂▃▄▇▃▇█▅▃▁ beats 50/246 | 10% |
| Decision Index 0.4.1: NLI4CT (macro-F1) submitted | 58.3% ✎ | ▁▁▁▂▂▃▃▄▇▇█▄ beats 38/246 | 5.3% |
| Decision Index 0.4.1: ANLI (macro-F1) submitted | 47.5% ✎ | ▁▂▃▅▅█▂····▁ beats 56/246 | 4.0% |
| Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted | 18.7% ✎ | ▁·▁·▁▁▃▄▅█▇▄ beats 19/246 | 1.3% |
| Decision Index 0.4.1: ContractNLI (macro-F1) submitted | 81.4% ✎ | ▁▁▁▁▁▁▁▂▂▇▇█ beats 173/246 | 1.0% |
| Decision Index 0.4.1: FinEntity (macro-F1) submitted | 85.5% ✎ | ▁···▁▁▁▁▃▆█▃ beats 103/246 | 0.9% |
| Decision Index 0.4.1: VAST (macro-F1) submitted | 74.0% ✎ | ▁▁▁▂▅▄▄▂▄▆█▄ beats 161/246 | 0.8% |
| Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted | 72.5% ✎ | ▁▁▁▁▁▁▁▁▁▃▆█ beats 113/246 | 0.7% |
1 more test
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: ACOS (per-review F1) submitted | 44.5% ✎ | ▁··▂▃▃▅▇█▇▃▃ beats 213/246 | 0.4% |
arts & human taste▃▇▄▃▅▅█▅▄▂▁▁ #245 of 247 · 7.3% of its score · 6 tests
Trails Zev (decision readout), LFM2.5-350M-RLCD, Nirnaya 0.4B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: New Yorker (accuracy) submitted | 52.6% ✎ | ▁▁▂▃▃▃▇▅█▅▃▁ beats 63/246 | 3.1% |
| Decision Index 0.4.1: BPoMP (accuracy) submitted | 42.3% ✎ | ▃█▄▄▅█▆▅▄▁▁▁ beats 2/246 | 1.7% |
| Decision Index 0.4.1: Humicroedit (accuracy) submitted | 51.2% ✎ | ▁·▁▃▂▂▅█▄▂▁▁ beats 32/246 | 1.4% |
| Decision Index 0.4.1: cfcolor (accuracy) submitted | 48.8% ✎ | ▁········▁▇█ beats 6/246 | 0.8% |
| Decision Index 0.4.1: Habermas Machine (accuracy) submitted | 38.5% ✎ | ▁▂▄█▇▅▁▁▄▄▁▁ beats 45/246 | 0.2% |
| Decision Index 0.4.1: POP909-CL (accuracy) submitted | 2.8% ✎ | ▄▅▅▃▆▅▃▅▂▅▃█ beats 59/237 | 0.1% |
knowledge & reasoning▁▂▃▂▂▃▃▅▅▆█▂ #234 of 263 · 48% of its score · 14 tests
Beats Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326), Amber 0.4B, vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B) here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), LFM2.5-2.6B-RLCD, Jev-Style 0.8B v3 here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: ARC-Challenge (accuracy) submitted | 49.9% ✎ | ▂▂▃▂▂▂▁▃▄▆█▆ beats 28/246 | 10% |
| Decision Index 0.4.1: ARC-Easy (accuracy) submitted | 69.7% ✎ | ▁▁▂▃▂▂▂▂▃▆█▅ beats 28/246 | 10% |
| Decision Index 0.4.1: MMLU (accuracy) submitted | 36.8% ✎ | ▁▄▄▃▃▂▅▇▅█▇▁ beats 25/246 | 6.8% |
| Decision Index 0.4.1: BBH (accuracy) submitted | 38.0% ✎ | ▄▆▄▄█▇▇▄▃▁▁▁ beats 28/246 | 5.4% |
| Decision Index 0.4.1: MMLU-Pro (accuracy) submitted | 15.2% ✎ | ▄▄▃▃▂▄▅▇██▅▁ beats 21/246 | 5.4% |
| Decision Index 0.4.1: WinoGrande (accuracy) submitted | 63.7% ✎ | █▅█▅▄█▆▄▃▃▁▁ beats 56/246 | 3.5% |
| Decision Index 0.4.1: GPQA Diamond (accuracy) submitted | 26.0% ✎ | ▂▆▅▅▆█▆▃▁··▁ beats 25/246 | 1.9% |
| Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted | 18.3% ✎ | ▁··▄█▆▆▆▅▅▃▁ beats 17/246 | 1.7% |
6 more tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: MuSR (accuracy) submitted | 54.0% ✎ | ▁▁▂█▅▄▁▁▁▁▁▁ beats 55/246 | 0.9% |
| Decision Index 0.4.1: CLadder (accuracy) submitted | 88.0% ✎ | ▁███▆▅▃▃▁▁▁▁ beats 212/246 | 0.9% |
| Decision Index 0.4.1: CRUXEval (accuracy) submitted | 45.3% ✎ | ██▄▃▃▄▁▁···▁ beats 89/246 | 0.8% |
| Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted | 5.1% ✎ | ▁▁▁▁▃▁▁▂▅█▂▁ beats 34/246 | 0.5% |
| Decision Index 0.4.1: ChessBench (accuracy) submitted | 8.6% ✎ | ▄▇▄▄▄▆▄█▄▁▁▁ beats 37/246 | 0.3% |
| Decision Index 0.4.1: HLE (accuracy) submitted | 14.6% ✎ | ▁▁▂▃▆█▇▅▅▃▁▁ beats 185/246 | 0.0% |
other tests2 not in a task · 5.8% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: private same skills (equated points) | 24.6900 points ✎ | ▂▂▂▃▃▃▄▅▅▇█▃ beats 52/247 | 3.7% |
| Decision Index 0.4.1: private new domains (equated points) | 9.2700 points ✎ | ▃█▃▃▂▆▃▃▄▄▄▄ beats 17/247 | 2.0% |
$ 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/Elfsong ↗
$ how the score was worked out · Decision Index 0.4.1 100%
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 |
|---|---|---|
| 42 | 100% | |
| prior · pull toward the middle | 0% | |
| weighted average | = 33.7 |
not counted (2)
| Decision Index 0.4.1 | Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct] | 67.3% | failed run: Publisher excludes this protocol because its prompt reveals GPT-4 as the best route. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json |
| Decision Index 0.4.1 | Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct] | 37.1% | failed run: Publisher reports a builder bug exposing dialogue turns after the classified turn; awaiting corrected rerun. Evidence: https://huggingface.co/spaces/multimodalart/jev-decision-index/blob/c130faf65f82e81d3bdefb01e758c712dc5c5199/data/index.json |
$ 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