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Turion Jev 31B

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Turion Jev 31B is an open-weights decision model from Turion.AI. Its published size is 31.27B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine turion-jev-31b; reported model Turion Jev 31B. Type: LoRA; 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.

69.9±1.4#16 of 355 decision modelsfrom 43 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of Turion Jev 31B, out of 357 with a score.

#	model	score	where	released
14	Nace.AI Drex Max v1 (27B) Nace-Deepinfra	70±1	model files
15	Bespoke Nimble v4 Max (27B) Bespoke Labs	70±1	model files	2026-10
16	Turion Jev 31B Turion.AI	70±1	model files
17	Perplexity Decider v1.2 (27B) Perplexity	70±1	model files
18	AutoTrust-JEV-27B v1.1 AutoTrust AI Lab	70±1	model files	2026-10-17

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #41 of 250 · 4.5% of its score · 6 tests

Beats Fastino GLiDE 1.2, vLLM-SR d3-ultra (Decision 3.0, 27B), KnowLine 35B-A3B Gen1.5 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Clef-flash 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	85.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 172/236	easy · avg 70%	▇ 1.3%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	70.4% ✎	▁▁▁▁▁·▁▁▁▄█▃ beats 233/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	82.1% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 156/246	easy · avg 72%	▇ 0.8%	noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	64.8% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 158/243	medium · avg 37%	▇ 0.8%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.6% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 208/246	very easy · avg 92%	▇ 0.7%	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▁▁▁·▁▁▁▁▃▃█▅ #15 of 258 · 7.0% of its score · 7 tests

Beats Fastino GLiDE 1.2, KnowLine 31B Gen1, Ainvest-Decision-27B v1.0 here, though they rank higher overall. Trails StartLux-Decision v1.1 4B, VisionJEV 1.0.0 (27B), OneShot 27B 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	51.5% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 246/246	medium · avg 38%	▇ 3.0%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	61.9% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 231/246	medium · avg 47%	▇ 2.5%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	81.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 153/246	easy · avg 74%	▇ 0.5%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	95.8% ✎	█▅▅▄▃▂▁▃▁▁·▁ beats 231/245	easy · avg 70%	▇ 0.5%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	82.7% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 114/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.4% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 165/238	easy · avg 83%	▇ 0.2%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	4.7% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #100 of 256 · 18% of its score · 9 tests

Trails Decider 4B, jiwo 4B v2, Sieve 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	80.2% ✎	▁▂▃▅▅█▃····▁ beats 237/246	medium · avg 60%	▇▇ 4.7%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	83.2% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 190/246	easy · avg 74%	▇▇ 4.4%	typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	68.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 223/246	medium · avg 44%	▇ 2.5%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	92.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 148/246	very easy · avg 85%	▇ 2.1%	sharp · maxed out
Decision Index 0.4.1: ACOS (per-review F1) submitted	44.2% ✎	▁··▂▃▃▅▇█▇▃▃ beats 212/246	hard · avg 22%	▇ 1.8%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.3% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 213/246	medium · avg 62%	▇ 1.0%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	82.6% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 191/246	easy · avg 71%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	81.3% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 195/246	easy · avg 66%	▇ 0.6%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	93.7% ✎	▁···▁▁▁▁▃▆█▃ beats 209/246	easy · avg 84%	▇ 0.4%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▃▁ #8 of 247 · 9.0% of its score · 6 tests

Beats Jeffan-31b-1710, Fastino GLiDE 1.2, KnowLine 31B Gen1 here, though they rank higher overall. Trails AnyJev Tacitus 31B, baselabs elephant-1 (9B), vera-large 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	79.9% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 218/246	medium · avg 61%	▇ 3.4%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	66.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 222/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	66.6% ✎	▁········▁▇█ beats 220/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	38.9% ✎	▄▅▅▃▆▅▃▅▃▅▃█ beats 159/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	98.6% ✎	▁█▄▄▅█▆▅▄▃▁▁ beats 239/246	easy · avg 83%	▇ 0.7%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	52.7% ✎	▁▂▄█▇▅▃▁▄▄▁▁ beats 181/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▃ #10 of 263 · 51% of its score · 15 tests

Beats Ainvest-Decision-27B v1.0, StartLux-Decision v1.1 27B, vLLM-SR d3-turbo v1.1 (27B) here, though they rank higher overall. Trails Jev 1.13, d1-ultra here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Etsabary · 1342 text decisions	83.5% ✎	▁··▂·▃▅▁▃▂▂█ beats 20/24	medium · avg 47%	▇▇▇▇▇▇ 14%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	74.4% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 238/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	82.8% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 204/246	easy · avg 66%	▇▇ 4.8%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	89.7% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 240/246	easy · avg 70%	▇▇ 4.7%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	55.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 234/246	medium · avg 39%	▇▇ 3.8%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	82.8% ✎	▁··▄█▆▆▆▅▅▃▁ beats 225/246	medium · avg 45%	▇ 3.1%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	90.9% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 203/246	easy · avg 78%	▇ 2.2%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	33.4% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 187/246	hard · avg 22%	▇ 2.1%	at its level

7 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	71.8% ✎	▁▁▂█▅▄▃▁▁▁▁▁ beats 224/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	98.0% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 242/246	very easy · avg 90%	▇ 1.2%	sharp · maxed out
Decision Index 0.4.1: CRUXEval (accuracy) submitted	89.3% ✎	██▄▃▃▄▁▁···▁ beats 237/246	medium · avg 58%	▇ 1.0%	noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	23.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 206/246	hard · avg 16%	▇ 1.0%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	87.8% ✎	▁███▆▅▃▃▁▁▁▁ beats 210/246	easy · avg 71%	▇ 0.9%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.3% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 233/246	very easy · avg 96%	▇ 0.5%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	15.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 213/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 10% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	65.0400 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 238/247	avg 41.206 points	▇▇▇ 6.4%	blunt
Decision Index 0.4.1: private new domains (equated points)	78.6000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 246/247	avg 38.861 points	▇ 3.5%	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/turion-ai ↗

$ how the score was worked out · Decision Index 0.4.1 85%, Etsabary · decision benchmarks 14%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 85%	CC BY 4.0
Etsabary · decision benchmarks	1	▇▇▇▇ 14%	MIT
prior · pull toward the middle		▇ 1%
weighted average		= 69.9

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]	4.7%	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

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