JADE

+ contribute

JADE is an open-weights decision model from theunnecessarythings, released 1 October 2026. Its published size is 27.8B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine jade; reported model JADE. 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

59.4±1.3#116 of 355 decision modelsfrom 44 benchmark results across 2 sources

$ how it compares

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

#	model	score	where	released
115	OneJev1.6-4B OmniJev	60±1	model files	2026-10-17
116	Eikos-27B-FP8 Qwen3.8-27B LoRA caiovicentino1	59±1	model files
117	JADE theunnecessarythings	59±1	model files	2026-10-01
118	xor (DecisionBench 679decd4) juspay	59±2	model files
119	gpt-5.6-luna (DecisionBench openrout) OpenAI	59±2	comparison only	2026-07-09

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #67 of 250 · 6.7% of its score · 6 tests

Beats mogan-decision-31B-it, Sieve 27B v2, Darwin-27B-ZTC here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber 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	83.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 137/236	easy · avg 70%	▇ 2.0%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 182/246	very easy · avg 92%	▇ 1.4%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	54.5% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 141/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	75.4% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 116/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	64.6% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 126/246	medium · avg 60%	▇ 1.0%	blunt · at its level
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▁▁▁·▁▁▁▁▃▃█▅ #88 of 258 · 6.7% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Decider 31B (NVFP4), Jev 1.13 here, though they rank higher overall. Trails Jev-Style 2B v4, 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	47.8% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 195/246	medium · avg 38%	▇ 2.6%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	55.8% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 165/246	medium · avg 47%	▇ 2.4%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	76.8% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 131/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	56.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 74/245	easy · avg 70%	▇ 0.5%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	87.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 98/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	78.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 80/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	34.8% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #70 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 Sieve 4B, Decider 35B-A3B, Sieve 9B v2 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	64.2% ✎	▁▂▃▅▅█▂····▁ beats 123/246	medium · avg 60%	▇▇ 5.3%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	83.9% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 199/246	easy · avg 74%	▇▇ 5.2%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	94.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 185/246	very easy · avg 85%	▇▇ 4.1%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	60.9% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 189/246	medium · avg 44%	▇ 2.4%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	26.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 153/246	hard · avg 22%	▇ 1.4%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	62.6% ✎	▁▁▁▂▅▄▄▃▄▆█▄ beats 113/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	74.6% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 111/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	67.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 85/246	easy · avg 66%	▇ 0.7%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	87.9% ✎	▁···▁▁▁▁▃▆█▃ beats 121/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #82 of 247 · 9.5% of its score · 6 tests

Beats Jev 1.13, jev-brain · Gemma-4-31B (decision readout), Jeffan-4B-2010 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	70.3% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 153/246	medium · avg 61%	▇▇ 3.9%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	62.0% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 148/246	medium · avg 60%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	62.9% ✎	▁········▁▇█ beats 141/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	19.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 130/237	hard · avg 21%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	91.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 165/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	44.9% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 134/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #83 of 263 · 43% of its score · 14 tests

Beats StartLux-Decision v1.1 4B, KnowLine 4B Gen5.5, Jeffan-4B-2010 here, though they rank higher overall. Trails Solar Decide, Clef-flash, Decider chat · Qwen3.6-27B (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	64.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 173/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	83.5% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 173/246	easy · avg 70%	▇▇▇ 6.4%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	79.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 186/246	easy · avg 66%	▇▇ 6.1%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	65.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 175/246	medium · avg 45%	▇ 3.6%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	45.9% ✎	▂▆▅▅▆█▆▃▁··▁ beats 162/246	medium · avg 39%	▇ 3.4%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.4% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 148/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.6% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 178/246	very easy · avg 90%	▇ 2.9%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	23.1% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 90/246	hard · avg 22%	▇ 1.6%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.0% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 199/246	very easy · avg 96%	▇ 1.3%	sharp · maxed out · noisy
Decision Index 0.4.1: MuSR (accuracy) submitted	62.9% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 159/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	69.3% ✎	██▄▃▃▄▁▁···▁ beats 166/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	72.3% ✎	▁███▆▅▃▃▁▁▁▁ beats 140/246	easy · avg 71%	▇ 0.9%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	16.5% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 127/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	9.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 20/246	very hard · avg 13%	▇ 0.0%	blunt

other tests4 not in a task · 12% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	53.8600 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 163/247	avg 41.206 points	▇▇ 5.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	58.1200 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 178/247	avg 38.861 points	▇ 3.1%	blunt
Benchmark Heaven jevbench v1.6.1: intelligence (points)	47.9344 points ✎	▃···▃·▃▃█▅▅█ beats 2/13	avg 32.166 points	▇ 2.5%	blunt
Benchmark Heaven jevbench v1.6.1: calibration (points)	50.5645 points ✎	▃······▂▆▂██ beats 0/13	avg 70.133 points	▇ 0.7%	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/theunnecessarythings ↗

$ how the score was worked out · Decision Index 0.4.1 96%, Benchmark Heaven (own decisio… 3%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%	CC BY 4.0
Benchmark Heaven (own decision evaluations)	2	▇ 3%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 59.4

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]	34.8%	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