OneJev1.6-9B

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OneJev1.6-9B is an open-weights decision model from OmniJev, released 17 October 2026. Its published size is 9.41B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine onejev1.6-9b; reported model OneJev1.6-9B. 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.

63.7±1.4#68 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of OneJev1.6-9B, out of 357 with a score, then more from OmniJev.

#	model	score	where	released
66	Bobcat 1.3 (31B) sanghwa-na	64±1	model files	2026-10-11
67	AnyJev L0 · Gemma-4-31B (decision readout) MorrisZJ	64±1	source code
68	OneJev1.6-9B OmniJev	64±1	model files	2026-10-17
69	JEV-27B-VL AutoTrust AI Lab	64±4	model files
70	KnowLine 35B-A3B Gen1 PelaAI	64±4	model files	2026-10-12
	more from OmniJev
23	OneJev1.6-27B OmniJev	69±2	model files	2026-10-17
58	OneJev1.5-27B OmniJev	65±4	model files	2026-10-13
107	OneJev1.5-9B OmniJev	61±4	model files	2026-10-13

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #6 of 250 · 6.2% 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	89.8% ✎	▁▁▁▁▁▁▁▂▃▂█▃ beats 233/236	easy · avg 70%	▇ 1.9%	sharp · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	70.5% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 171/243	medium · avg 37%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	98.2% ✎	▁▂▁▁▁▂▂▄▅▆█▃ beats 240/246	very easy · avg 92%	▇ 1.1%	sharp · maxed out · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	71.0% ✎	▁▁▁▁▁·▁▁▁▄█▃ beats 237/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	90.0% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 218/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #114 of 258 · 7.4% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Quyet-1.0-Large here, though they rank higher overall. Trails vLLM-SR vela3-fast (Vela 3.0, 0.4B), crystal-0.8b, Kas 4B 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	41.6% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 112/246	medium · avg 38%	▇ 3.0%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	53.6% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 140/246	medium · avg 47%	▇ 2.6%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	88.6% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 225/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	95.2% ✎	█▅▅▄▃▂▁▃▁▁·▁ beats 230/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	96.1% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 220/238	easy · avg 83%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	90.2% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 184/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	69.4% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #48 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	72.8% ✎	▁▂▃▅▅█▂····▁ beats 174/246	medium · avg 60%	▇▇ 5.5%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	81.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 167/246	easy · avg 74%	▇▇ 5.2%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	95.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 202/246	very easy · avg 85%	▇ 3.4%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	51.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 142/246	medium · avg 44%	▇ 2.7%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	33.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 176/246	hard · avg 22%	▇ 1.7%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	81.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 235/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	84.3% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 215/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	84.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 226/246	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	94.9% ✎	▁···▁▁▁▁▃▆█▃ beats 234/246	easy · avg 84%	▇ 0.5%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #90 of 247 · 10% 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 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 185/246	medium · avg 61%	▇▇ 4.1%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	64.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 200/246	medium · avg 60%	▇ 2.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	80.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 221/237	hard · avg 21%	▇ 1.3%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	64.6% ✎	▁········▁▇█ beats 168/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	91.0% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 155/246	easy · avg 83%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	62.9% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 227/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #96 of 263 · 44% 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 decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout), Solar Decide, Clef-flash 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	59.4% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 151/246	medium · avg 46%	▇▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	79.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 157/246	easy · avg 70%	▇▇ 6.2%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	86.4% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 220/246	easy · avg 66%	▇▇ 6.1%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	48.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 175/246	medium · avg 39%	▇▇ 3.9%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	62.2% ✎	▁··▄█▆▆▆▅▅▃▁ beats 167/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	88.8% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 194/246	easy · avg 78%	▇ 2.8%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.1% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 165/246	very easy · avg 90%	▇ 2.2%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	40.7% ✎	▁▁▁▁▁▁▁▂▅█▃▁ beats 227/246	hard · avg 22%	▇ 1.9%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	90.7% ✎	▁▁▂█▅▄▁▁▁▁▁▃ beats 244/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	56.7% ✎	██▄▃▃▄▁▁···▁ beats 135/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	91.9% ✎	▁███▆▅▃▃▃▁▁▁ beats 226/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 135/246	very easy · avg 96%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	22.5% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 196/246	hard · avg 16%	▇ 0.9%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	10.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 50/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 10% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	56.4600 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 183/247	avg 41.206 points	▇▇▇ 6.4%	blunt
Decision Index 0.4.1: private new domains (equated points)	47.9300 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 152/247	avg 38.861 points	▇ 3.5%	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/OmniJev ↗

$ 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		= 63.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.0%	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]	69.4%	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

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