Cerno 4B v1.1

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Cerno 4B v1.1 is an open-weights decision model from apertixai, released 19 October 2026. Its published size is 4.21B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine cerno-4b-v11; reported model Cerno 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

57.0±1.3#136 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Cerno 4B v1.1, out of 357 with a score, then more from apertixai.

#	model	score	where	released
136	simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e) featherless-ai	58±2	model files
137	Sieve 9B v2 Sthānika AI	57±1	model files	2026-10-13
138	Cerno 4B v1.1 apertixai	57±1	model files	2026-10-19
139	jqv (DecisionBench 9216db57) Octalab-Inc	57±2	model files
140	Trio-Spark DI (9B) MachineFi Labs	57±1	request access
	more from apertixai
40	Cerno 27B apertixai	67±1	model files
111	Cerno 9B v1.1 apertixai	60±1	model files	2026-10-19

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #154 of 250 · 7.2% of its score · 6 tests

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	82.5% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 130/236	easy · avg 70%	▇ 2.2%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	92.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 89/246	very easy · avg 92%	▇ 1.7%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	94.3% ✎	█▁▁▃▄▄▆▄▁▃▁▃ beats 210/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	89.6% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 213/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.6% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 178/246	medium · avg 60%	▇ 1.0%	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▁▁▁·▁▁▁▁▃▃█▅ #67 of 258 · 6.7% of its score · 7 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 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	47.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 183/246	medium · avg 38%	▇ 2.5%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	57.3% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 183/246	medium · avg 47%	▇ 2.3%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	88.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 220/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	69.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 128/245	easy · avg 70%	▇ 0.6%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	95.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 212/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	92.2% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 215/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	48.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #81 of 256 · 23% 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, Amber 4B, Decider 35B-A3B 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	69.4% ✎	▁▂▃▅▅█▂····▁ beats 152/246	medium · avg 60%	▇▇ 5.4%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	78.3% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 132/246	easy · avg 74%	▇▇ 5.4%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	93.9% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 170/246	very easy · avg 85%	▇▇ 4.8%	sharp
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	57.9% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 175/246	medium · avg 44%	▇ 2.4%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	26.2% ✎	▁··▂▃▃▅▇█▇▃▃ beats 148/246	hard · avg 22%	▇ 1.3%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	82.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 187/246	easy · avg 71%	▇ 1.1%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 212/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	83.9% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 219/246	easy · avg 66%	▇ 0.8%	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	86.3% ✎	▁···▁▁▁▁▃▆█▃ beats 107/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #137 of 247 · 10% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5 here, though they rank higher overall. Trails Crivo-68M, Crivo-150M v2, vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B) 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	74.8% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 189/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	64.2% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 194/246	medium · avg 60%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	85.6% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 110/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	63.1% ✎	▁········▁▇█ beats 145/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	5.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 71/237	hard · avg 21%	▇ 1.0%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	62.3% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 221/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #135 of 263 · 45% of its score · 14 tests

Beats Winnow-12B (DecisionBench b6ac22b0) 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	52.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 124/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	73.8% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 111/246	easy · avg 70%	▇▇▇ 6.9%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	80.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 193/246	easy · avg 66%	▇▇▇ 6.3%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	58.7% ✎	▁··▄█▆▆▆▅▅▃▁ beats 155/246	medium · avg 45%	▇ 3.6%	sharp · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	94.0% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 125/246	very easy · avg 90%	▇ 3.5%	sharp · maxed out
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	38.8% ✎	▂▆▅▅▆█▆▃▁··▁ beats 107/246	medium · avg 39%	▇ 3.3%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	85.6% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 167/246	easy · avg 78%	▇ 3.1%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.4% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 151/246	very easy · avg 96%	▇ 1.7%	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	15.3% ✎	▁▁▁▁▁▁▁▃▅█▂▁ beats 57/246	hard · avg 22%	▇ 1.5%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	54.4% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 57/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	44.6% ✎	██▄▃▃▄▁▁···▁ beats 83/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	79.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 171/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	9.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 55/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	9.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 25/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.6% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	46.9000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 130/247	avg 41.206 points	▇▇ 5.6%	blunt
Decision Index 0.4.1: private new domains (equated points)	32.5300 points ✎	▃█▃▃▃▆▃▃▄▄▄▄ beats 98/247	avg 38.861 points	▇ 3.1%	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/apertixai ↗

$ 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		= 57.0

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]	48.9%	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

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data updated 2026-11-03 02:37 UTC · sources and licences · json