Aplomb 1

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Aplomb 1 is an open-weights decision model from EmpirioLabs AI. Its published size is 5.3B parameters. Licence: other.

Catalogue identity notes

Exact Decision Index tested engine aplomb-1; reported model Aplomb 1. 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.

51.6±1.1#192 of 355 decision modelsfrom 54 benchmark results across 2 sources

$ how it compares

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

#	model	score	where	RAM	released
192	Jebadiah 4B v2 (Ollaya Q8_0) frontier-infra	52±3	local	~5.5GB	2026-10
193	JEV-9B AutoTrust AI Lab	52±1	model files
194	Aplomb 1 EmpirioLabs AI	52±1	request access
195	Shisa DE-2 (repeat) Shisa.AI	51±4	model files
196	ZTC-Judge-9B (DecisionBench 05d154a5) FINAL-Bench	51±2	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #152 of 250 · 7.1% of its score · 6 tests

Beats Cerno 4B v1.1, Trio-Spark DI (9B), Decider 35B-A3B here, though they rank higher overall. Trails JevK5 Lite, Gevva E2B, 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: API-Bank (accuracy) submitted	60.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 70/236	easy · avg 70%	▇ 2.2%	sharp · at its level · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	92.4% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 97/246	very easy · avg 92%	▇ 2.1%	sharp · maxed out · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	77.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 127/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	23.9% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 95/243	medium · avg 37%	▇ 1.0%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	65.0% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 133/246	medium · avg 60%	▇ 0.8%	blunt · at its level
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▁▁▁·▁▁▁▁▃▃█▅ #180 of 258 · 5.5% of its score · 7 tests

Beats JevK5 9B v0.3.3 here, though they rank higher overall. Trails Mola-68M, Bosun v3.1 1.7B LoRA, Dinah-1 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	43.0% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 127/246	medium · avg 38%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	43.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 77/246	medium · avg 47%	▇ 1.9%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	65.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 83/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	70.7% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 132/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	54.6% ✎	▁▁▁▁▁▁▁▃▃▆█▄ beats 30/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	71.0% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 41/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	67.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #147 of 256 · 21% of its score · 9 tests

Beats Solar Decide, JoshuaSP diffgemma (decision readout), PurpleMIST-Flash-1.0 here, though they rank higher overall. Trails Decider 2B, Crivo-1B, LatentMesh Blitz 2B v1 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	84.4% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 107/246	very easy · avg 85%	▇▇ 5.5%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	79.4% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 148/246	easy · avg 74%	▇▇ 4.9%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	58.7% ✎	▁▂▃▅▅█▂····▁ beats 101/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	43.9% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 108/246	medium · avg 44%	▇ 1.9%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	75.7% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 123/246	easy · avg 71%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: ACOS (per-review F1) submitted	13.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 76/246	hard · avg 22%	▇ 0.9%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	48.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 71/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	72.3% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 112/246	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	81.9% ✎	▁···▁▁▁▁▃▆█▃ beats 78/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #130 of 247 · 8.1% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5, Cerno 4B v1.1 here, though they rank higher overall. 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	61.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 109/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	62.1% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 152/246	medium · avg 60%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	87.0% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 117/246	easy · avg 83%	▇ 1.2%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	65.6% ✎	▁········▁▇█ beats 195/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	8.3% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 94/237	hard · avg 21%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.1% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 95/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #131 of 263 · 41% of its score · 14 tests

Beats Winnow-12B (DecisionBench b6ac22b0), Cerno 4B v1.1, Amber Hybrid 4B (decision readout) here, though they rank higher overall. Trails djev diffgemma (decision readout), Kev 9B v2, Bespoke Nimble 9B v2 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	54.8% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 132/246	medium · avg 46%	▇▇▇ 8.7%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	76.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 126/246	easy · avg 70%	▇▇▇ 6.5%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	64.8% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 104/246	easy · avg 66%	▇▇ 5.7%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	93.6% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 117/246	very easy · avg 90%	▇▇ 4.4%	sharp
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	39.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 108/246	medium · avg 45%	▇ 2.9%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	78.2% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 120/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	48.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 178/246	medium · avg 39%	▇ 2.6%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	97.7% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 113/246	very easy · avg 96%	▇ 2.4%	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	30.4% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 150/246	hard · avg 22%	▇ 1.1%	typical
Decision Index 0.4.1: MuSR (accuracy) submitted	53.7% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 50/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	49.5% ✎	██▄▃▃▄▁▁···▁ beats 107/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	64.2% ✎	▁███▆▅▃▃▁▁▁▁ beats 92/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: ChessBench (accuracy) submitted	12.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 85/246	hard · avg 16%	▇ 0.5%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.2% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 71/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #52 of 79 · 10% of its score · 12 tests

Beats RSI-Jev v6.1 VL 4B, baselabs joey-1 (2B), QEV-2B here, though they rank higher overall. Trails JPT-4B Qwen3.5-4B LoRA, LiquidAI d1-3B 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	60.1200 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 12/61	avg 63.423 points	▇ 1.3%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	23.4900 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 16/61	avg 22.797 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	79.5000 points ✎	▁·▁▁▁▁·▂▁▃▅█ beats 30/61	avg 66.987 points	▇ 1.1%	blunt
Decision Index Vision 0.4: private same skills (points)	50.8000 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 20/61	avg 48.067 points	▇ 1.1%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	24.6500 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 17/61	avg 28.443 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	60.3200 points ✎	▁·▂▂▁▃▃▅▅▃▂█ beats 31/61	avg 53.651 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	68.6700 points ✎	▂▁▁▁▁▃▁▅▅▆██ beats 24/61	avg 62.137 points	▇ 0.8%	blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	90.7100 points ✎	▁·▁▂▁▁▃▁▂▃▅█ beats 27/61	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	29.6100 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 39/61	avg 19.676 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	52.4800 points ✎	▁···▁▂▂▂█▄▂▃ beats 23/61	avg 44.994 points	▇ 0.6%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	75.8800 points ✎	▁▁▁▁▂▁▁▁▄█▃▃ beats 35/61	avg 67.662 points	▇ 0.5%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	88.5100 points ✎	▁··▁▁▁▁▁▃▄█▁ beats 15/61	avg 85.184 points	▇ 0.4%	blunt

other tests2 not in a task · 6.9% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	41.7300 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 107/247	avg 41.206 points	▇▇ 4.5%	blunt
Decision Index 0.4.1: private new domains (equated points)	39.2900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 122/247	avg 38.861 points	▇ 2.5%	blunt

$ where to run it

Request access to model files ↗
Gated files: the publisher requires access approval. 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/empiriolabsai ↗

$ how the score was worked out · Decision Index 0.4.1 89%, Decision Index Vision 0.4 10%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 89%	CC BY 4.0
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇▇ 10%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 51.6

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]	67.2%	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