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Matilda Decision v1

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Matilda Decision v1 is an open-weights decision model from Maincode. Its published size is 26.09B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine matilda-decision-v1; reported model Matilda Decision v1. 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.

68.1±1.5#31 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Matilda Decision v1, out of 357 with a score, then more from Maincode.

#	model	score	where	released
29	StartLux-Decision v1.1 9B StartLux	68±1	model files
30	OneShot 27B OneShot	68±2	model files
31	Matilda Decision v1 Maincode	68±2	model files
32	d1.1 (hosted) Liquid AI	68±2	api price unknown
33	VisionJEV 1.0.0 (27B) taoszhang	68±1	model files
	more from Maincode
142	matilda-jev-v1.5 (27B) Maincode	57±4	model files	2026-10-09

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #7 of 250 · 5.6% of its score · 6 tests

Beats Jeffan-31b-1710, Sieve 31B v3, Fastino GLiDE 1.2 here, though they rank higher overall. Trails Clef-flash, Clef-omni, Clef 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	86.2% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 197/236	easy · avg 70%	▇ 1.6%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	68.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 209/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	87.5% ✎	█▁▁▃▄▄▆▄▃▂▁▃ beats 203/243	medium · avg 37%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	89.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 204/246	easy · avg 72%	▇ 0.9%	noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	98.2% ✎	▁▂▁▁▁▂▂▄▅▆█▃ beats 241/246	very easy · avg 92%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.6% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #23 of 258 · 7.9% of its score · 7 tests

Beats KnowLine 31B Gen1, Ainvest-Decision-27B v1.0, Perplexity Decider v1.1 (27B) here, though they rank higher overall. Trails JEV-35B, StartLux-Decision v1.1 4B, Torchcast Decision 27B 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	48.4% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 204/246	medium · avg 38%	▇ 3.3%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	61.5% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 226/246	medium · avg 47%	▇ 2.8%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	88.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 221/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	74.2% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 148/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	90.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 191/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.8% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 171/238	easy · avg 83%	▇ 0.3%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	52.3% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #41 of 256 · 21% of its score · 9 tests

Beats Ainvest-Decision-27B v1.0, H2O Lightning 31B v1.1, Turion Jev 31B here, though they rank higher overall. Trails Decider 35B-A3B, Sieve 9B v2, Clef-flash 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	76.3% ✎	▁▂▃▅▅█▂····▁ beats 207/246	medium · avg 60%	▇▇ 5.5%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	85.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 214/246	easy · avg 74%	▇▇ 5.1%	typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	69.6% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 233/246	medium · avg 44%	▇ 2.8%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	95.9% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 208/246	very easy · avg 85%	▇ 2.7%	sharp · maxed out
Decision Index 0.4.1: ACOS (per-review F1) submitted	38.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 193/246	hard · avg 22%	▇ 1.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	81.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 234/246	medium · avg 62%	▇ 1.1%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	85.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 231/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	85.4% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 236/246	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	94.2% ✎	▁···▁▁▁▁▃▆█▃ beats 218/246	easy · avg 84%	▇ 0.5%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #55 of 247 · 10% of its score · 6 tests

Beats OneJev1.6-27B 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	72.4% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 167/246	medium · avg 61%	▇▇ 4.0%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	65.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 210/246	medium · avg 60%	▇ 2.4%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	57.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 174/237	hard · avg 21%	▇ 1.4%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	64.8% ✎	▁········▁▇█ beats 176/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	95.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 195/246	easy · avg 83%	▇ 0.8%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	38.0% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 41/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▃ #11 of 263 · 43% of its score · 14 tests

Beats Ainvest-Decision-27B v1.0, StartLux-Decision v1.1 27B, vLLM-SR d3-turbo v1.1 (27B) here, though they rank higher overall. Trails Jev 1.13 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	80.7% ✎	▄▄▃▃▂▄▅▇██▅▃ beats 245/246	medium · avg 46%	▇▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	83.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 206/246	easy · avg 66%	▇▇ 5.8%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	89.8% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 241/246	easy · avg 70%	▇▇ 5.6%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	53.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 224/246	medium · avg 39%	▇▇ 4.3%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	76.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 212/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	90.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 199/246	easy · avg 78%	▇ 2.6%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	23.0% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 89/246	hard · avg 22%	▇ 2.3%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.9% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 190/246	very easy · avg 90%	▇ 1.6%	sharp · maxed out

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	66.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 197/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	80.5% ✎	██▄▃▃▄▁▁···▁ beats 198/246	medium · avg 58%	▇ 1.2%	noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	22.7% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 197/246	hard · avg 16%	▇ 1.1%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	80.6% ✎	▁███▆▅▃▃▁▁▁▁ beats 181/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.1% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 204/246	very easy · avg 96%	▇ 0.6%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	16.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 227/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 11% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	59.9800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 208/247	avg 41.206 points	▇▇▇ 7.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	71.9000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 218/247	avg 38.861 points	▇▇ 3.9%	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/Maincode ↗

$ 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		= 68.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.6%	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]	52.3%	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