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VisionJEV 1.0.0 (27B)

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VisionJEV 1.0.0 (27B) is an open-weights decision model from taoszhang. Its published size is 26.09B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine visionjev-1.0.0; reported model VisionJEV 1.0.0 (27B). 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.

67.9±1.3#33 of 355 decision modelsfrom 54 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of VisionJEV 1.0.0 (27B), out of 357 with a score.

#	model	score	where
31	Matilda Decision v1 Maincode	68±2	model files
32	d1.1 (hosted) Liquid AI	68±2	api price unknown
33	VisionJEV 1.0.0 (27B) taoszhang	68±1	model files
34	RBDash-Decision v0.2 RBDash-Team	68±4	model files
35	mogan-decision-31B-it Mogan AI	67±1	model files

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$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #55 of 250 · 4.8% of its score · 6 tests

Beats AutoTrust-JEV-27B v1.1, OneShot 27B here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber Hybrid 4B (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	87.5% ✎	▁▁▁▁▁▁▁▂▃▂█▃ beats 213/236	easy · avg 70%	▇ 1.4%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.3% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 169/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	100.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 233/243	medium · avg 37%	▇ 0.9%	sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	74.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 109/246	easy · avg 72%	▇ 0.8%	noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 194/246	very easy · avg 92%	▇ 0.7%	sharp · maxed out · 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▁▁▁·▁▁▁▁▃▃█▅ #13 of 258 · 6.8% 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 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	50.3% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 238/246	medium · avg 38%	▇ 2.8%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	62.1% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 233/246	medium · avg 47%	▇ 2.4%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	90.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 245/246	easy · avg 74%	▇ 0.5%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	75.3% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 155/245	easy · avg 70%	▇ 0.5%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	81.0% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 108/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	96.4% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 226/238	easy · avg 83%	▇ 0.2%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	27.1% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #59 of 256 · 18% of its score · 9 tests

Beats Ainvest-Decision-27B v1.0, Turion Jev 31B, MISA AI 2.0 Decision Plus · oak 1.1 (31B) here, though they rank higher overall. Trails Decider 35B-A3B, Sieve 9B v2, Clef-flash 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	73.2% ✎	▁▂▃▅▅█▂····▁ beats 178/246	medium · avg 60%	▇▇ 4.7%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	86.2% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 228/246	easy · avg 74%	▇▇ 4.4%	typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	69.0% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 228/246	medium · avg 44%	▇ 2.4%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	94.8% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 190/246	very easy · avg 85%	▇ 2.3%	sharp · maxed out
Decision Index 0.4.1: ACOS (per-review F1) submitted	51.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 225/246	hard · avg 22%	▇ 1.7%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	80.6% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 230/246	medium · avg 62%	▇ 0.9%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	78.7% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 151/246	easy · avg 71%	▇ 0.9%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	86.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 246/246	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	94.9% ✎	▁···▁▁▁▁▃▆█▃ beats 231/246	easy · avg 84%	▇ 0.4%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #40 of 247 · 8.9% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), Nace.AI Drex Max v1 (27B) here, though they rank higher overall. Trails Kas 4B, baselabs joey-1 (2B), Xor 1.2 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	75.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 191/246	medium · avg 61%	▇ 3.5%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	61.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 133/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	63.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 184/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	64.5% ✎	▁········▁▇█ beats 167/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	95.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 209/246	easy · avg 83%	▇ 0.7%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.9% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 108/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #32 of 263 · 37% of its score · 14 tests

Beats vera-large, KnowLine 26B-A4B Gen2.5, OneJev1.6-27B here, though they rank higher overall. Trails Solar Decide, 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: MMLU-Pro (accuracy) submitted	71.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 218/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	83.2% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 207/246	easy · avg 66%	▇▇ 5.0%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	87.5% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 213/246	easy · avg 70%	▇▇ 4.9%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	52.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 217/246	medium · avg 39%	▇ 3.7%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	75.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 207/246	medium · avg 45%	▇ 3.2%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	93.2% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 218/246	easy · avg 78%	▇ 2.3%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	34.2% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 195/246	hard · avg 22%	▇ 1.9%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.3% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 210/246	very easy · avg 90%	▇ 1.4%	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	70.1% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 216/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	84.7% ✎	██▄▃▃▄▁▁···▁ beats 213/246	medium · avg 58%	▇ 1.0%	noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	28.7% ✎	▄▇▄▄▄▆▄█▄▃▁▁ beats 235/246	hard · avg 16%	▇ 0.9%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	96.7% ✎	▁███▆▅▃▃▁▁▁▃ beats 244/246	easy · avg 71%	▇ 0.9%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 219/246	very easy · avg 96%	▇ 0.6%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	17.2% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 235/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #19 of 79 · 14% of its score · 12 tests

Beats StartLux-Decision v1.1 27B, Nace.AI Drex Max v1 (27B), AutoTrust-JEV-27B v1.1 here, though they rank higher overall. Trails Clef-flash, Mercury Decide (free endpoint), Clef here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	84.5200 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 51/61	avg 63.423 points	▇ 1.8%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	44.6400 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 53/61	avg 22.797 points	▇ 1.7%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	85.7500 points ✎	▁·▁▁▁▁·▂▁▃▅█ beats 52/61	avg 66.987 points	▇ 1.5%	blunt
Decision Index Vision 0.4: private same skills (points)	66.0700 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 49/61	avg 48.067 points	▇ 1.5%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	54.3300 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 56/61	avg 28.443 points	▇ 1.3%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	74.2000 points ✎	▁·▂▂▁▃▃▅▅▃▂█ beats 58/61	avg 53.651 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	76.4400 points ✎	▂▁▁▁▁▃▁▅▅▆██ beats 40/61	avg 62.137 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	98.9100 points ✎	▁·▁▂▁▁▃▁▂▂▅█ beats 60/61	avg 83.859 points	▇ 0.9%	blunt

4 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted	31.6000 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 44/61	avg 19.676 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	74.0600 points ✎	▁···▁▂▂▂█▄▂▃ beats 57/61	avg 44.994 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	80.1700 points ✎	▁▁▁▁▂▁▁▁▄█▃▃ beats 56/61	avg 67.662 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	93.1900 points ✎	▁··▁▁▁▁▁▂▄█▁ beats 58/61	avg 85.184 points	▇ 0.5%	blunt

other tests2 not in a task · 9.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	62.4700 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 226/247	avg 41.206 points	▇▇ 6.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	73.5000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 228/247	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/taoszhang ↗

$ how the score was worked out · Decision Index 0.4.1 85%, Decision Index Vision 0.4 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
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇▇▇ 14%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 67.9

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]	27.1%	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

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