Solomon v1.1

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Solomon v1.1 is an open-weights decision model from Doccy Health, released 21 September 2026. Its published size is 27.78B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine solomon-v11-bf16-encoding; reported model Solomon v1.1. Type: head / adapter; 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

53.9±1.2#168 of 355 decision modelsfrom 49 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of Solomon v1.1, out of 357 with a score.

#	model	score	where	released
168	Jevfire Qwen3.8-27B (decision readout) kikoncuo	54±1	source code
169	Open-Jev-9B (JevBench mini) Zefan Cai	54±2	source code
170	Solomon v1.1 Doccy Health	54±1	model files	2026-09-21
171	Sieve 4B Sthānika AI	54±1	model files	2026-10-13
172	Bespoke-Nimble-9B (DecisionBench 594dfdcf) Bespoke Labs	54±2	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #14 of 250 · 3.9% of its score · 3 tests

Beats Jeffan-31b-1710, Sieve 31B v3, Fastino GLiDE 1.2 here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	98.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 234/246	very easy · avg 92%	▇ 1.9%	sharp · maxed out · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	82.6% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 161/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	65.6% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 151/246	medium · avg 60%	▇ 0.9%	blunt · at its level

retrieval & classification▁▁▁·▁▁▁▁▃▃█▅ #84 of 258 · 5.3% of its score · 5 tests

Beats AutoTrust-JEV-27B v1.1, oenogarum (Gemma 4 31B), Decider 31B (NVFP4) here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 3B SH (v4) 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	46.9% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 176/246	medium · avg 38%	▇ 2.2%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	56.2% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 169/246	medium · avg 47%	▇ 2.0%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	71.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 104/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	68.2% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 122/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	59.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #119 of 256 · 22% of its score · 9 tests

Beats garum (Gemma 4 31B), Shisa DE-2.1 (repeat), garas (Gemma 4 31B) here, though they rank higher overall. Trails Decider 4B, jiwo 4B v2, Saif 4B 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	91.0% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 135/246	very easy · avg 85%	▇▇ 5.2%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	81.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 165/246	easy · avg 74%	▇▇ 5.1%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	67.1% ✎	▁▂▃▅▅█▂····▁ beats 138/246	medium · avg 60%	▇▇ 4.9%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	48.2% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 125/246	medium · avg 44%	▇ 2.1%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	20.7% ✎	▁··▂▃▃▅▇█▇▃▃ beats 114/246	hard · avg 22%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	71.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 82/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	69.4% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 133/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	75.5% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 131/246	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: FinEntity (macro-F1) submitted	91.9% ✎	▁···▁▁▁▁▃▆█▃ beats 177/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #67 of 247 · 7.9% of its score · 5 tests

Beats mogan-decision-31B-it, FlexDM · Gemma-4-31B (decision readout), Jev 1.13 here, though they rank higher overall. Trails Amber 0.4B, Crivo-1B, Kas 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	51.7% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 61/246	medium · avg 61%	▇ 3.7%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	54.2% ✎	▁·▁▃▃▂▅█▄▂▁▁ beats 50/246	medium · avg 60%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	94.1% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 182/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	50.2% ✎	▁········▁▇█ beats 16/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	37.3% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 33/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #173 of 263 · 42% of its score · 14 tests

Trails openvons Qwen3-4B (decision readout), Jevstral 8B, Jobe Qwen3.5-4B (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	70.7% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 214/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	70.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 97/246	easy · avg 70%	▇▇▇ 6.7%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	72.5% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 148/246	easy · avg 66%	▇▇ 6.0%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	84.6% ✎	▂▂▂▂▂▂▃▃▄▆█▆ beats 75/246	very easy · avg 90%	▇▇ 4.0%	sharp · maxed out
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	27.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 69/246	medium · avg 45%	▇ 3.2%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	81.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 131/246	easy · avg 78%	▇ 3.0%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	42.9% ✎	▂▆▅▅▆█▆▃▁··▁ beats 136/246	medium · avg 39%	▇ 2.9%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	86.6% ✎	▁▁▂▁▂▃▂▂▃▆█▅ beats 59/246	very easy · avg 96%	▇ 2.1%	sharp · maxed out · noisy

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	20.5% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 78/246	hard · avg 22%	▇ 1.2%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	60.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 138/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	69.3% ✎	██▄▃▃▄▁▁···▁ beats 167/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	70.4% ✎	▁███▆▅▃▃▁▁▁▁ beats 128/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: ChessBench (accuracy) submitted	40.2% ✎	▄▇▄▄▄▆▄█▄▁▁▃ beats 246/246	hard · avg 16%	▇ 0.6%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	14.7% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 188/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #41 of 79 · 11% of its score · 12 tests

Beats Surogate Rune 26B-A4B v3, Clef-omni, matilda-jev-v1.5 (27B) here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	79.7200 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 38/61	avg 63.423 points	▇ 1.4%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	-3.0300 points ✎	▃▁▅▁▄▁▄█▄▃▇▇ beats 0/61	avg 22.797 points	▇ 1.3%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	84.2500 points ✎	▁·▁▁▁▁·▂▁▃▅█ beats 46/61	avg 66.987 points	▇ 1.2%	blunt
Decision Index Vision 0.4: private same skills (points)	63.7900 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 43/61	avg 48.067 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	36.3600 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 29/61	avg 28.443 points	▇ 1.0%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	76.1400 points ✎	▁·▂▂▁▃▃▅▅▃▂█ beats 61/61	avg 53.651 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	74.9400 points ✎	▂▁▁▁▁▃▁▅▅▆██ beats 37/61	avg 62.137 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	94.5400 points ✎	▁·▁▂▁▁▃▁▂▂▅█ beats 39/61	avg 83.859 points	▇ 0.7%	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	18.2400 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 18/61	avg 19.676 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	59.2400 points ✎	▁···▁▂▂▂█▄▂▃ beats 42/61	avg 44.994 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	74.7400 points ✎	▁▁▁▁▂▁▁▁▄█▃▃ beats 31/61	avg 67.662 points	▇ 0.6%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	92.2500 points ✎	▁··▁▁▁▁▁▂▄█▁ beats 42/61	avg 85.184 points	▇ 0.4%	blunt

other tests2 not in a task · 7.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	36.3200 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 84/247	avg 41.206 points	▇▇ 4.9%	blunt
Decision Index 0.4.1: private new domains (equated points)	53.5900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 165/247	avg 38.861 points	▇ 2.7%	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/DoccyHealth ↗

$ how the score was worked out · Decision Index 0.4.1 88%, Decision Index Vision 0.4 11%

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	37	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 88%	CC BY 4.0
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇▇ 11%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 53.9

not counted (1)

Decision Index 0.4.1

Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]

59.2%

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