whatmodel.sh / decision / Jegue 0.1 (9B)

Jegue 0.1 (9B)

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Jegue 0.1 (9B) is an open-weights decision model from fdemelo. Its published size is 9.65B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine jegue-0.1; reported model Jegue 0.1 (9B). Type: LoRA + head; 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.

55.7±1.3#148 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Jegue 0.1 (9B), out of 357 with a score.

#	model	score	where	released
148	xor-26b-a4b-v1.1 Juspay Technologies	56±4	model files	2026-10-09
149	decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout) aminry	56±1	source code	2026-10-04
150	Jegue 0.1 (9B) fdemelo	56±1	model files
151	djev-dev (DecisionBench f7f5b7f5) Davipar	56±2	model files
152	open-alternative-jev (DecisionBench 4a85df18) IkerMoel	56±2	source code

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #114 of 250 · 7.4% of its score · 6 tests

Beats Senova-4B v2, Tern-35B-A3B, GEV-26B-Decide here, though they rank higher overall. Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, razorback16 diffgemma (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: API-Bank (accuracy) submitted	78.1% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 109/236	easy · avg 70%	▇ 2.3%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	95.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 133/246	very easy · avg 92%	▇ 1.8%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	40.9% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 115/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	87.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 193/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	65.5% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 146/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #79 of 258 · 6.6% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, oenogarum (Gemma 4 31B), Decider 31B (NVFP4) here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 3B SH (v4), Standard One 8B SH (v4) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	45.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 155/246	medium · avg 38%	▇ 2.4%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	56.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 172/246	medium · avg 47%	▇ 2.3%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	65.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 82/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	97.0% ✎	█▅▅▄▃▂▁▁▃▁·▁ beats 240/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	93.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 187/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.4% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 153/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	69.8% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #74 of 256 · 23% of its score · 9 tests

Beats Turion Jev 31B, AJev lm6q (Gemma 4 31B), oenogarum (Gemma 4 31B) here, though they rank higher overall. Trails Sieve 4B, Amber 4B, Decider 35B-A3B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	78.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 142/246	easy · avg 74%	▇▇ 5.4%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	66.1% ✎	▁▂▃▅▅█▂····▁ beats 133/246	medium · avg 60%	▇▇ 5.3%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	94.2% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 178/246	very easy · avg 85%	▇▇ 5.1%	sharp
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	57.8% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 174/246	medium · avg 44%	▇ 2.3%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	52.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 226/246	hard · avg 22%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	81.4% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 172/246	easy · avg 71%	▇ 1.1%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	56.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 98/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	82.7% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 208/246	easy · avg 66%	▇ 0.8%	at its level · noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	94.3% ✎	▁···▁▁▁▁▃▆█▃ beats 222/246	easy · avg 84%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #163 of 247 · 9.4% of its score · 6 tests

Trails Crivo-17M, Crivo-32M v2, Crivo-68M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: New Yorker (accuracy) submitted	65.5% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 132/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	65.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 212/246	medium · avg 60%	▇ 1.9%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	77.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 84/246	easy · avg 83%	▇ 1.2%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	56.0% ✎	▁········▁▇█ beats 58/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 43/237	hard · avg 21%	▇ 0.9%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	46.6% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 155/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #122 of 263 · 45% of its score · 14 tests

Beats OneJev1.6-4B, Winnow-12B (DecisionBench b6ac22b0), Cerno 4B v1.1 here, though they rank higher overall. Trails PurpleMIST-Flash-1.0, JPT-9B Qwen3.5-9B LoRA, Jevfire Qwen3.8-27B (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	55.3% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 138/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	76.2% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 129/246	easy · avg 70%	▇▇▇ 7.0%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	67.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 114/246	easy · avg 66%	▇▇▇ 6.4%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	94.1% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 128/246	very easy · avg 90%	▇▇ 3.8%	sharp · maxed out
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	60.4% ✎	▁··▄█▆▆▆▅▅▃▁ beats 160/246	medium · avg 45%	▇ 3.5%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	38.8% ✎	▂▆▅▅▆█▆▃▁··▁ beats 108/246	medium · avg 39%	▇ 3.2%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	82.5% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 136/246	easy · avg 78%	▇ 3.1%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 139/246	very easy · avg 96%	▇ 1.9%	sharp · maxed out · noisy

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	32.5% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 179/246	hard · avg 22%	▇ 1.4%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	58.1% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 110/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	53.9% ✎	██▄▃▃▄▁▁···▁ beats 129/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	65.4% ✎	▁███▆▅▃▃▁▁▁▁ beats 98/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	12.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 81/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	7.0% ✎	▃▁▂▃▆█▇▅▅▃▁▁ beats 0/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.4% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	48.2900 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 137/247	avg 41.206 points	▇▇ 5.4%	blunt
Decision Index 0.4.1: private new domains (equated points)	37.9600 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 116/247	avg 38.861 points	▇ 3.0%	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/fdemelo ↗

$ how the score was worked out · Decision Index 0.4.1 99%

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	licence
Decision Index 0.4.1 · submitted; independent execution unverified	42	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 55.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.0%	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]	69.8%	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

Update model information Add a place to run it Add a test result Propose a benchmark Correct a benchmark score Edit data on GitHub

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 2026-11-03 02:37 UTC · sources and licences · json