whatmodel.sh / decision / open-jev (pngwn)

open-jev (pngwn)

+ contribute

open-jev (pngwn) is an open-weights decision model from pngwn. Its published size is 4.66B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine pngwn-space-uncapped-full; reported model open-jev (pngwn). 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.

41.1±1.1#260 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of open-jev (pngwn), out of 357 with a score.

#	model	score	where	RAM
260	Qwen3-Reranker-4B (DecisionBench 22e68366) Alibaba (Qwen)	41±2	model files
261	mini-jev Qwen3-4B (decision readout) r-ms	41±1	source code
262	open-jev (pngwn) pngwn	41±1	model files
263	Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326) llm-semantic-router	41±1	local	~5.8GB
264	Decider 2B Mapika	41±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #178 of 250 · 8.9% of its score · 6 tests

Beats LiquidAI d1-3B, Decider 4B, JevK5 v0.3 here, though they rank higher overall. Trails JevK5 Lite, Mola-150M, Gevva E2B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	89.7% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 72/246	very easy · avg 92%	▇▇ 4.0%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	48.4% ✎	▁▁▁▁▁▁▁▃▃▂█▂ beats 47/236	easy · avg 70%	▇ 2.4%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	46.6% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 36/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	60.5% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 70/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	3.4% ✎	█▁▃▃▄▄▆▄▁▂▁▃ beats 57/243	medium · avg 37%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.9% ✎	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▁▁▁·▁▁▃▁▃▃█▅ #222 of 258 · 5.2% of its score · 7 tests

Beats Intelif Qwen3-4B, mini-jev Qwen3-4B (decision readout) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Crivo-32M v2, Jev-Style 0.8B v3 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	40.6% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 103/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	30.7% ✎	▁▁▁▁▁▁▂▃▃▃█▅ beats 36/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	55.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 25/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	57.6% ✎	▁▁▁▁▁▁▁▃▃▆█▄ beats 31/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.2% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 35/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	50.5% ✎	▁·▁▁▁▁▁▃▂█▇█ beats 15/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	59.0% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #182 of 256 · 24% of its score · 9 tests

Beats Nari Decision 4B v3.2, Solar Decide Flash, Lev1 3.7B here, though they rank higher overall. Trails DecisionTune 1.0, vera-spark, jdi-ptr14-0.8b here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	77.1% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 72/246	very easy · avg 85%	▇▇▇ 8.6%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	74.3% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 95/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	58.8% ✎	▁▂▃▅▅█▂····▁ beats 102/246	medium · avg 60%	▇▇ 4.5%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	37.6% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 82/246	medium · avg 44%	▇ 1.6%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	63.7% ✎	▁▁▁▁▁▁▁▂▃▇▇█ beats 55/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	38.3% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 24/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	74.6% ✎	▁···▁▁▁▁▃▆█▃ beats 53/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	0.4% ✎	▃▁▁▁▁▁▁▁▁▃▆█ beats 1/246	easy · avg 66%	▇ 0.7%	at its level · noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ACOS (per-review F1) submitted	12.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 69/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #214 of 247 · 8.0% of its score · 6 tests

Beats Valen-4B, TokenRhythm NeoHorse-Jev-4B, OneJev1.6-0.8B here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Qwen-2.5-1B-RLCD (decision readout) 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	45.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 52/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	51.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 31/246	easy · avg 83%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	55.2% ✎	▁·▁▃▂▃▅█▄▂▁▁ beats 59/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	58.3% ✎	▁········▁▇█ beats 82/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	5.6% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 79/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.1% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 94/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #191 of 263 · 47% of its score · 14 tests

Beats StartLux-Decision v1.1 0.8B, Sieve 2B v3, LatentMesh Blitz 2B v1 here, though they rank higher overall. Trails DM-JEPA 1.1, Sieve 2B, Valen-2B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	91.2% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 98/246	very easy · avg 90%	▇▇▇ 8.3%	sharp
Decision Index 0.4.1: MMLU (accuracy) submitted	44.5% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 43/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	12.7% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 7/246	medium · avg 46%	▇▇▇ 7.2%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	96.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 92/246	very easy · avg 96%	▇▇ 6.2%	sharp · noisy
Decision Index 0.4.1: BBH (accuracy) submitted	59.3% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 80/246	easy · avg 66%	▇▇ 6.0%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	70.8% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 90/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	44.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 125/246	medium · avg 45%	▇ 2.3%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	43.9% ✎	▂▆▅▅▆█▆▃▁··▁ beats 141/246	medium · avg 39%	▇ 2.2%	blunt · 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	58.1% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 111/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	48.3% ✎	██▄▃▃▄▁▁···▁ beats 101/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	63.2% ✎	▁███▆▅▃▃▁▁▁▁ beats 79/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	30.7% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 155/246	hard · avg 22%	▇ 0.7%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	10.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 60/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 63/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.4% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	29.3300 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 62/247	avg 41.206 points	▇▇ 4.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	33.7500 points ✎	▃█▃▃▃▆▃▃▄▄▄▄ beats 99/247	avg 38.861 points	▇ 2.3%	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/pngwn ↗

$ 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		= 41.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.9%	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]	59.0%	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