whatmodel.sh / decision / Verdin-4B v1.1

Verdin-4B v1.1

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Verdin-4B v1.1 is an open-weights decision model from victorbennett. Its published size is 4.21B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine verdin-4b-v1.1; reported model Verdin-4B v1.1. 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.

60.9±1.3#101 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Verdin-4B v1.1, out of 357 with a score.

#	model	score	where	RAM
99	litjev (DecisionBench 1d4bf0f2) zhengxuyu	61±2	model files
100	Surogate Rune 26B-A4B v3 Surogate	61±1	request access
101	Verdin-4B v1.1 victorbennett	61±1	model files
102	garas (Gemma 4 31B) plantwaterer	61±1	model files
103	vLLM-SR d3-flash (9B) vLLM Semantic Router	61±1	local	~18GB

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #76 of 250 · 6.7% of its score · 6 tests

Beats Sieve 27B v2, allec-oavg (Gemma 4 31B), Jev 1.13 here, though they rank higher overall. Trails baselabs joey-1 (2B), Hopper 12B (trained), 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: API-Bank (accuracy) submitted	84.3% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 142/236	easy · avg 70%	▇ 2.0%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.6% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 169/246	very easy · avg 92%	▇ 1.3%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	71.6% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 172/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	67.8% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 198/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	90.7% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 224/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.7% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #54 of 258 · 7.1% of its score · 7 tests

Beats H2O Lightning 31B v1.1, AutoTrust-JEV-27B v1.1, d1.1 (hosted) here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 8B SH (v4), StartLux-Decision v1.1 2B 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	45.6% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 163/246	medium · avg 38%	▇ 2.8%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	58.5% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 194/246	medium · avg 47%	▇ 2.5%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	86.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 195/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	79.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 170/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 170/238	easy · avg 83%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.6% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 157/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	9.3% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #88 of 256 · 22% of its score · 9 tests

Beats Turion Jev 31B, AJev lm6q (Gemma 4 31B), oenogarum (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	73.6% ✎	▁▂▃▅▅█▂····▁ beats 184/246	medium · avg 60%	▇▇ 5.5%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	82.3% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 176/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	93.4% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 164/246	very easy · avg 85%	▇▇ 3.9%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	55.8% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 165/246	medium · avg 44%	▇ 2.6%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	12.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 71/246	hard · avg 22%	▇ 1.5%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	78.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 195/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	84.3% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 213/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	80.8% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 185/246	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	93.4% ✎	▁···▁▁▁▁▃▆█▃ beats 206/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #47 of 247 · 10% 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), Clef-flash 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	71.0% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 161/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	62.9% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 166/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	65.1% ✎	▁········▁▇█ beats 183/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	78.6% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 211/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	95.5% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 202/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	44.7% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 130/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #103 of 263 · 44% of its score · 14 tests

Beats Senova-4B v2 here, though they rank higher overall. Trails Decider 35B-A3B, decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout), Solar Decide 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	59.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 157/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	79.7% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 153/246	easy · avg 70%	▇▇▇ 6.5%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	79.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 187/246	easy · avg 66%	▇▇ 6.2%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	65.2% ✎	▁··▄█▆▆▆▅▅▃▁ beats 176/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	41.3% ✎	▂▆▅▅▆█▆▃▁··▁ beats 119/246	medium · avg 39%	▇ 3.6%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.7% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 151/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	95.5% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 148/246	very easy · avg 90%	▇ 2.7%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	30.1% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 148/246	hard · avg 22%	▇ 1.8%	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	68.8% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 206/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.5% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 153/246	very easy · avg 96%	▇ 1.2%	sharp · maxed out · noisy
Decision Index 0.4.1: CRUXEval (accuracy) submitted	62.8% ✎	██▄▃▃▄▁▁···▁ beats 150/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	87.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 211/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	20.2% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 171/246	hard · avg 16%	▇ 0.8%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 95/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 9.4% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	53.7000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 161/247	avg 41.206 points	▇▇ 6.0%	blunt
Decision Index 0.4.1: private new domains (equated points)	49.4300 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 154/247	avg 38.861 points	▇ 3.3%	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/victorbennett ↗

$ 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		= 60.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.7%	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]	9.3%	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