Cerno 9B v1.1

+ contribute

Cerno 9B v1.1 is an open-weights decision model from apertixai, released 19 October 2026. Its published size is 8.95B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine cerno-9b-v11; reported model Cerno 9B 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.

59.8±1.3#110 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Cerno 9B v1.1, out of 357 with a score, then more from apertixai.

#	model	score	where	released
109	AJev lora1 (Gemma 4 26B-A4B) andyzhang232	60±1	model files
110	decider-35b-a3b (DecisionBench d9783c58) Mapika	60±2	model files	2026-09-20
111	Cerno 9B v1.1 apertixai	60±1	model files	2026-10-19
112	openjev-sglang (DecisionBench 1355db6a) ekzhang	60±2	model files
113	JEV-27B AutoTrust AI Lab	60±1	model files
	more from apertixai
40	Cerno 27B apertixai	67±1	model files
138	Cerno 4B v1.1 apertixai	57±1	model files	2026-10-19

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #119 of 250 · 6.8% of its score · 6 tests

Beats Senova-4B v2, Tern-35B-A3B, GEV-26B-Decide here, though they rank higher overall. Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, razorback16 diffgemma (decision readout) 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	74.8% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 103/236	easy · avg 70%	▇ 2.1%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	95.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 130/246	very easy · avg 92%	▇ 1.4%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	80.7% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 192/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	88.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 202/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 172/246	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▁▁▁·▁▁▁▁▃▃█▅ #52 of 258 · 7.0% of its score · 7 tests

Beats H2O Lightning 31B v1.1, AutoTrust-JEV-27B v1.1, d1.1 (hosted) 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	46.3% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 170/246	medium · avg 38%	▇ 2.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	58.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 198/246	medium · avg 47%	▇ 2.5%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	87.6% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 210/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	66.8% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 112/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	95.8% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 216/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	92.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 221/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	60.6% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #52 of 256 · 22% of its score · 9 tests

Beats Ainvest-Decision-27B v1.0, Turion Jev 31B, MISA AI 2.0 Decision Plus · oak 1.1 (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	71.3% ✎	▁▂▃▅▅█▂····▁ beats 167/246	medium · avg 60%	▇▇ 5.4%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	81.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 160/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	95.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 201/246	very easy · avg 85%	▇▇ 4.2%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	59.0% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 178/246	medium · avg 44%	▇ 2.5%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	25.5% ✎	▁··▂▃▃▅▇█▇▃▃ beats 146/246	hard · avg 22%	▇ 1.4%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.7% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 218/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	81.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 175/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	83.9% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 220/246	easy · avg 66%	▇ 0.8%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	86.8% ✎	▁···▁▁▁▁▃▆█▃ beats 110/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #110 of 247 · 10% of its score · 6 tests

Beats Bobcat 1.3 (31B), Nace.AI Drex v2.0 (35B-A3B), decisio 0.6.0 (Gemma 4 31B) (decision readout) 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	74.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 184/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	64.4% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 196/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	62.2% ✎	▁········▁▇█ beats 127/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	14.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 114/237	hard · avg 21%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	89.8% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 136/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	62.4% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 223/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #106 of 263 · 44% of its score · 14 tests

Beats Senova-4B v2 here, though they rank higher overall. Trails Decider 35B-A3B, decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout), Solar Decide 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	59.5% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 154/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	79.4% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 150/246	easy · avg 70%	▇▇▇ 6.6%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	80.3% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 194/246	easy · avg 66%	▇▇ 6.2%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	65.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 177/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	43.4% ✎	▂▆▅▅▆█▆▃▁··▁ beats 138/246	medium · avg 39%	▇ 3.5%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	87.8% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 180/246	easy · avg 78%	▇ 3.0%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	95.6% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 151/246	very easy · avg 90%	▇ 2.9%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	26.1% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 110/246	hard · avg 22%	▇ 1.7%	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	98.5% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 154/246	very easy · avg 96%	▇ 1.3%	sharp · maxed out · noisy
Decision Index 0.4.1: MuSR (accuracy) submitted	58.5% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 116/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	49.1% ✎	██▄▃▃▄▁▁···▁ beats 105/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	78.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 170/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	12.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 90/246	hard · avg 16%	▇ 0.8%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	9.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 18/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 9.1% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	51.9100 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 156/247	avg 41.206 points	▇▇ 5.9%	blunt
Decision Index 0.4.1: private new domains (equated points)	40.4800 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 129/247	avg 38.861 points	▇ 3.2%	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		= 59.8

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]	60.6%	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