JEV-35B

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JEV-35B is an open-weights decision model from AutoTrust AI Lab. Its published size is 35.95B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine jev-35b; reported model JEV-35B. 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.

62.5±1.4#83 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of JEV-35B, out of 357 with a score, then more from AutoTrust AI Lab.

#	model	score	where	released
81	decisio 0.6.0 (Gemma 4 31B) (decision readout) aminry	63±1	source code	2026-10-05
82	deck31b (Gemma 4 31B) (decision readout) krishna-gogineni-765	63±1	source code
83	JEV-35B AutoTrust AI Lab	63±1	model files
84	SynACK Decide 26B-A4B v7 SkyPanther	62±1	model files
85	Decider chat · Gemma-4-31B (decision readout) Mapika	62±1	source code
	more from AutoTrust AI Lab
18	AutoTrust-JEV-27B v1.1 AutoTrust AI Lab	70±1	model files	2026-10-17
69	JEV-27B-VL AutoTrust AI Lab	64±4	model files
98	GEV-26B-Decide AutoTrust AI Lab	61±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #85 of 250 · 6.4% of its score · 6 tests

Beats Sieve 27B v2, Jev 1.13, Span-02 (Gemma 4 26B-A4B) here, though they rank higher overall. Trails OneJev1.6-0.8B, Jev-Omni, baselabs joey-1 (2B) 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 188/236	easy · avg 70%	▇ 1.9%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 161/246	very easy · avg 92%	▇ 1.2%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	50.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 132/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	65.3% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 144/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	89.7% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 215/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.8% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #18 of 258 · 7.3% of its score · 7 tests

Beats Fastino GLiDE 1.2, KnowLine 31B Gen1, Ainvest-Decision-27B v1.0 here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	48.8% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 214/246	medium · avg 38%	▇ 2.9%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	61.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 229/246	medium · avg 47%	▇ 2.6%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	88.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 219/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	83.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 185/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	94.3% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 197/238	easy · avg 83%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	92.2% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 217/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	60.7% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #24 of 256 · 22% of its score · 9 tests

Beats KnowLine 31B Gen1, Ainvest-Decision-27B v1.0, WeMM-JEV-27B here, though they rank higher overall. Trails Clef-flash, Clef-omni 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	69.6% ✎	▁▂▃▅▅█▂····▁ beats 154/246	medium · avg 60%	▇▇ 5.5%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	80.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 158/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	97.2% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 227/246	very easy · avg 85%	▇ 3.6%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	55.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 162/246	medium · avg 44%	▇ 2.6%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	29.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 165/246	hard · avg 22%	▇ 1.6%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	69.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 137/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	81.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 174/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	83.9% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 218/246	easy · avg 66%	▇ 0.8%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	90.2% ✎	▁···▁▁▁▁▃▆█▃ beats 148/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #129 of 247 · 10% of its score · 6 tests

Trails vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B), Crivo-400M, Amber 0.4B 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	79.5% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 216/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	61.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 137/246	medium · avg 60%	▇ 2.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	14.1% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 115/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	62.2% ✎	▁········▁▇█ beats 126/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	87.1% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 118/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	59.8% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 202/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #60 of 263 · 44% of its score · 14 tests

Beats OneJev1.6-27B, baselabs elephant-1 (9B), StartLux-Decision v1.1 9B here, though they rank higher overall. Trails Solar Decide, Clef-flash, Clef-omni 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	68.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 198/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	86.5% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 201/246	easy · avg 70%	▇▇▇ 6.3%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	75.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 163/246	easy · avg 66%	▇▇ 6.1%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	52.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 212/246	medium · avg 39%	▇▇ 3.8%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	46.2% ✎	▁··▄█▆▆▆▅▅▃▁ beats 130/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	92.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 211/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.7% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 234/246	very easy · avg 90%	▇ 2.4%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	29.3% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 134/246	hard · avg 22%	▇ 1.9%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	59.8% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 132/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	71.4% ✎	██▄▃▃▄▁▁···▁ beats 173/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.0% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 183/246	very easy · avg 96%	▇ 1.0%	sharp · maxed out · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	72.0% ✎	▁███▆▅▃▃▁▁▁▁ beats 137/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	19.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 167/246	hard · avg 16%	▇ 0.9%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	10.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 56/246	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)	55.7800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 176/247	avg 41.206 points	▇▇▇ 6.3%	blunt
Decision Index 0.4.1: private new domains (equated points)	60.3600 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 187/247	avg 38.861 points	▇ 3.4%	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/autotrust ↗

$ 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		= 62.5

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.8%	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]	60.7%	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