whatmodel.sh / decision / JEV Ettin 150M

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.

33.7±1.0#285 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of JEV Ettin 150M, out of 357 with a score, then more from Elfsong.

#modelscorewhereRAMreleased
285wyat-1-800m teilomillet34±1model files2026-10-18
286tasksource Decider nano v5 (150M) tasksource34±1model files
287JEV Ettin 150M Elfsong34±1model files2026-10-23
288Valen-0.8B Valen34±1model files
289JPT-0.8B Qwen3.5-0.8B LoRA kirp33±1model files
more from Elfsong
299JEV FLAN-T5 Large public v2 (342M) Elfsong32±1model files2026-10-18
319JEV Ettin 400M Elfsong29±1model 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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted76.3% ✎▁▂▁▁▁▃▂▄▅▆█▁ beats 38/246very easy · avg 92%▇▇ 5.4%sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted41.7% ✎▁▁▁▁▁▁▁▃▃▂█▂ beats 34/236easy · avg 70%▇ 2.2%sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted69.4% ✎▁▁▁▂▃▅▅▆█▇█▃ beats 94/246easy · avg 72%▇ 1.1%at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted61.0% ✎▁▁▁▁▁·▁▁▁▄█▁ beats 73/246medium · avg 60%▇ 0.7%blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted81.8% ✎█▁▁▃▄▄▆▄▁▂▁▃ beats 199/243medium · avg 37%▇ 0.3%sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted67.3% ✎no other model yet—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
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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted43.8% ✎▁▁▁▁▁▁▂▂▃▃█▅ beats 78/246medium · avg 47%▇ 1.4%at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted28.4% ✎▁▁▁▁▁▁▁▃▂▄▇█ beats 41/246medium · avg 38%▇ 1.4%blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted92.5% ✎▁▁▁▁▁▁▁▂▃▆█▄ beats 166/238easy · avg 83%▇ 0.6%sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted85.2% ✎▆▆▇▅▄▄▃▇▄█▆▄ beats 187/246easy · avg 74%▇ 0.5%blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted50.1% ✎█▅▅▄▃▂▁▁▁▁·▁ beats 28/245easy · avg 70%▇ 0.5%at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted91.8% ✎▁·▁▁▁▁▁▁▂█▇█ beats 210/238easy · avg 79%▇ 0.3%at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted37.1% ✎no other model yet—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
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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: HellaSwag (accuracy) submitted64.3% ✎▂▄▂▃▄▇▃▇█▅▃▁ beats 50/246very easy · avg 85%▇▇▇▇ 10%sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted58.3% ✎▁▁▁▂▂▃▃▄▇▇█▄ beats 38/246easy · avg 74%▇▇ 5.3%at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted47.5% ✎▁▂▃▅▅█▂····▁ beats 56/246medium · avg 60%▇▇ 4.0%at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted18.7% ✎▁·▁·▁▁▃▄▅█▇▄ beats 19/246medium · avg 44%▇ 1.3%at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted81.4% ✎▁▁▁▁▁▁▁▂▂▇▇█ beats 173/246easy · avg 71%▇ 1.0%at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted85.5% ✎▁···▁▁▁▁▃▆█▃ beats 103/246easy · avg 84%▇ 0.9%at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted74.0% ✎▁▁▁▂▅▄▄▂▄▆█▄ beats 161/246medium · avg 62%▇ 0.8%at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted72.5% ✎▁▁▁▁▁▁▁▁▁▃▆█ beats 113/246easy · avg 66%▇ 0.7%at its level · noisy
1 more test
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ACOS (per-review F1) submitted44.5% ✎▁··▂▃▃▅▇█▇▃▃ beats 213/246hard · avg 22%▇ 0.4%noisy
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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: New Yorker (accuracy) submitted52.6% ✎▁▁▂▃▃▃▇▅█▅▃▁ beats 63/246medium · avg 61%▇ 3.1%at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted42.3% ✎▃█▄▄▅█▆▅▄▁▁▁ beats 2/246easy · avg 83%▇ 1.7%sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted51.2% ✎▁·▁▃▂▂▅█▄▂▁▁ beats 32/246medium · avg 60%▇ 1.4%blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted48.8% ✎▁········▁▇█ beats 6/246medium · avg 60%▇ 0.8%blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted38.5% ✎▁▂▄█▇▅▁▁▄▄▁▁ beats 45/246medium · avg 47%▇ 0.2%blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted2.8% ✎▄▅▅▃▆▅▃▅▂▅▃█ beats 59/237hard · avg 21%▇ 0.1%sharp · too hard for it · noisy
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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted49.9% ✎▂▂▃▂▂▂▁▃▄▆█▆ beats 28/246very easy · avg 90%▇▇▇▇ 10%sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted69.7% ✎▁▁▂▃▂▂▂▂▃▆█▅ beats 28/246very easy · avg 96%▇▇▇▇ 10%sharp · noisy
Decision Index 0.4.1: MMLU (accuracy) submitted36.8% ✎▁▄▄▃▃▂▅▇▅█▇▁ beats 25/246easy · avg 70%▇▇▇ 6.8%sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted38.0% ✎▄▆▄▄█▇▇▄▃▁▁▁ beats 28/246easy · avg 66%▇▇ 5.4%at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted15.2% ✎▄▄▃▃▂▄▅▇██▅▁ beats 21/246medium · avg 46%▇▇ 5.4%sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted63.7% ✎█▅█▅▄█▆▄▃▃▁▁ beats 56/246easy · avg 78%▇ 3.5%at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted26.0% ✎▂▆▅▅▆█▆▃▁··▁ beats 25/246medium · avg 39%▇ 1.9%blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted18.3% ✎▁··▄█▆▆▆▅▅▃▁ beats 17/246medium · avg 45%▇ 1.7%sharp
6 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MuSR (accuracy) submitted54.0% ✎▁▁▂█▅▄▁▁▁▁▁▁ beats 55/246medium · avg 60%▇ 0.9%blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted88.0% ✎▁███▆▅▃▃▁▁▁▁ beats 212/246easy · avg 71%▇ 0.9%at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted45.3% ✎██▄▃▃▄▁▁···▁ beats 89/246medium · avg 58%▇ 0.8%at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted5.1% ✎▁▁▁▁▃▁▁▂▅█▂▁ beats 34/246hard · avg 22%▇ 0.5%typical
Decision Index 0.4.1: ChessBench (accuracy) submitted8.6% ✎▄▇▄▄▄▆▄█▄▁▁▁ beats 37/246hard · avg 16%▇ 0.3%blunt
Decision Index 0.4.1: HLE (accuracy) submitted14.6% ✎▁▁▂▃▆█▇▅▅▃▁▁ beats 185/246very hard · avg 13%▇ 0.0%blunt
other tests2 not in a task · 5.8% of its score
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: private same skills (equated points)24.6900 points ✎▂▂▂▃▃▃▄▅▅▇█▃ beats 52/247avg 41.206 points▇ 3.7%blunt
Decision Index 0.4.1: private new domains (equated points)9.2700 points ✎▃█▃▃▂▆▃▃▄▄▄▄ beats 17/247avg 38.861 points▇ 2.0%blunt

$ 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

sourceresultsshare of the scorelicence
Decision Index 0.4.1 · submitted; independent execution unverified42CC BY 4.0
prior · pull toward the middle
weighted average= 33.7

not counted (2)

Decision Index 0.4.1Decision 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 0.4.1Decision 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