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oenogarum (Gemma 4 31B)

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oenogarum (Gemma 4 31B) is an open-weights decision model from plantwaterer. Its published size is 31.27B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine oenogarum; reported model oenogarum (Gemma 4 31B). 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

· Weights licence ↗ · Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

67.1±1.4#36 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of oenogarum (Gemma 4 31B), out of 357 with a score, then more from plantwaterer.

#	model	score	where	released
34	RBDash-Decision v0.2 RBDash-Team	68±4	model files
35	mogan-decision-31B-it Mogan AI	67±1	model files
36	oenogarum (Gemma 4 31B) plantwaterer	67±1	model files
37	Sieve 27B v2 Sthānika AI	67±1	model files	2026-10-18
38	H2O Lightning 31B H2O.ai	67±4	request access
	more from plantwaterer
48	allec-oavg (Gemma 4 31B) plantwaterer	66±1	model files
87	garum (Gemma 4 31B) plantwaterer	62±1	model files
102	garas (Gemma 4 31B) plantwaterer	61±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #46 of 250 · 5.7% of its score · 6 tests

Beats Fastino GLiDE 1.2, vLLM-SR d3-ultra (Decision 3.0, 27B), AutoTrust-JEV-27B v1.1 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Bespoke Nimble 9B v3 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	85.8% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 185/236	easy · avg 70%	▇ 1.7%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.7% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 179/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	63.6% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 152/243	medium · avg 37%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	80.5% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 143/246	easy · avg 72%	▇ 0.9%	noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.5% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 200/246	very easy · avg 92%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #86 of 258 · 7.8% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1 here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 3B SH (v4), Solomon v1.1 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	47.2% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 189/246	medium · avg 38%	▇ 3.2%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	55.6% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 163/246	medium · avg 47%	▇ 2.8%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	78.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 133/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	87.7% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 203/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	78.1% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 75/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	90.7% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 138/238	easy · avg 83%	▇ 0.3%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	23.7% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #89 of 256 · 22% of its score · 9 tests

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

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ANLI (macro-F1) submitted	77.6% ✎	▁▂▃▅▅█▂····▁ beats 219/246	medium · avg 60%	▇▇ 5.5%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	85.4% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 218/246	easy · avg 74%	▇▇ 5.2%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	93.2% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 159/246	very easy · avg 85%	▇ 2.8%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	73.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 244/246	medium · avg 44%	▇ 2.8%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	26.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 149/246	hard · avg 22%	▇ 1.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	74.8% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 169/246	medium · avg 62%	▇ 1.1%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	71.8% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 85/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	79.4% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 167/246	easy · avg 66%	▇ 0.7%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	94.2% ✎	▁···▁▁▁▁▃▆█▃ beats 216/246	easy · avg 84%	▇ 0.5%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #28 of 247 · 10% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), WeMM-JEV-27B here, though they rank higher overall. Trails Kas 4B, Clef-omni, Clef 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	79.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 211/246	medium · avg 61%	▇▇ 4.0%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	66.0% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 216/246	medium · avg 60%	▇ 2.4%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	59.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 175/237	hard · avg 21%	▇ 1.3%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	65.4% ✎	▁········▁▇█ beats 188/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	96.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 219/246	easy · avg 83%	▇ 0.8%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	45.8% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 144/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #24 of 263 · 43% of its score · 14 tests

Beats KnowLine 35B-A3B Gen1.5, Bespoke Nimble v4 Max (27B), vera-large here, though they rank higher overall. Trails d1 (hosted), Jev 1.13 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	73.8% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 235/246	medium · avg 46%	▇▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	80.8% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 198/246	easy · avg 66%	▇▇ 5.9%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	88.3% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 229/246	easy · avg 70%	▇▇ 5.8%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	53.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 223/246	medium · avg 39%	▇▇ 4.2%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	83.4% ✎	▁··▄█▆▆▆▅▅▃▁ beats 228/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	88.2% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 184/246	easy · avg 78%	▇ 2.7%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	34.8% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 204/246	hard · avg 22%	▇ 2.2%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.4% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 220/246	very easy · avg 90%	▇ 1.7%	sharp · maxed out

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	64.9% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 173/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	86.3% ✎	██▄▃▃▄▁▁···▁ beats 221/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	21.2% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 175/246	hard · avg 16%	▇ 1.0%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	84.2% ✎	▁███▆▅▃▃▁▁▁▁ beats 200/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 223/246	very easy · avg 96%	▇ 0.7%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	13.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 156/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 11% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	62.5000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 229/247	avg 41.206 points	▇▇▇ 7.0%	blunt
Decision Index 0.4.1: private new domains (equated points)	76.5000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 245/247	avg 38.861 points	▇▇ 3.8%	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/plantwaterer ↗

$ 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		= 67.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.0%	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]	23.7%	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