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OneJev1.6-0.8B

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OneJev1.6-0.8B is an open-weights decision model from OmniJev, released 17 October 2026. Its published size is 0.85B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine onejev1.6-0.8b; reported model OneJev1.6-0.8B. 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.

44.9±1.1#244 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of OneJev1.6-0.8B, out of 357 with a score, then more from OmniJev.

#	model	score	where	RAM	released
244	Metask-Jev-4B Metask-AI-Lab	45±1	model files
245	Jobe Qwen3.5-4B (decision readout) MantisShrimpdev	45±1	source code
246	OneJev1.6-0.8B OmniJev	45±1	model files		2026-10-17
247	GLiClass v4 edge (0.4B) Knowledgator Engineering	45±1	local	~2.7GB
248	Jevstral 8B AmirBraham	44±1	model files
	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
68	OneJev1.6-9B OmniJev	64±1	model files		2026-10-17

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #84 of 250 · 8.6% of its score · 6 tests

Beats Sieve 27B v2, Jev 1.13, Span-02 (Gemma 4 26B-A4B) here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 165/246	very easy · avg 92%	▇ 3.4%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	86.8% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 205/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	86.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 188/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	68.5% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 211/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	29.5% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 103/243	medium · avg 37%	▇ 0.7%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.1% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #148 of 258 · 5.6% of its score · 7 tests

Beats Quyet-1.0-Large, Decider chat · Qwen3.6-27B (decision readout), Sieve 9B v2 here, though they rank higher overall. Trails Amber 0.4B, Saina Helm 2 Omni (0.8B), jdi-ptr14-0.8b 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	35.9% ✎	▁▁▁▁▁▁▁▂▃▄▇█ beats 76/246	medium · avg 38%	▇ 1.8%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	50.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 108/246	medium · avg 47%	▇ 1.8%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	75.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 122/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	91.1% ✎	█▅▅▄▃▃▁▁▁▁·▁ beats 218/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.4% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 163/238	easy · avg 83%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.3% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 152/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	70.8% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #186 of 256 · 24% of its score · 9 tests

Beats Nari Decision 4B v3.2, Solar Decide Flash, Lev1 3.7B here, though they rank higher overall. Trails DecisionTune 1.0, vera-spark, JEV FLAN-T5 Large public v2 (342M) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	76.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 69/246	very easy · avg 85%	▇▇▇ 7.8%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	68.1% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 68/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	52.7% ✎	▁▂▃▅▅█▂····▁ beats 76/246	medium · avg 60%	▇▇ 4.8%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	14.8% ✎	▁·▁·▁▁▃▄▅█▇▄ beats 12/246	medium · avg 44%	▇ 1.8%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	82.7% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 192/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	74.6% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 166/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	89.8% ✎	▁···▁▁▁▁▃▆█▃ beats 145/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	77.4% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 148/246	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: ACOS (per-review F1) submitted	24.3% ✎	▁··▂▃▃▅▇█▇▃▃ beats 139/246	hard · avg 22%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #222 of 247 · 8.3% of its score · 6 tests

Beats Valen-4B, TokenRhythm NeoHorse-Jev-4B here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Bekko System One v0 17M 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	59.3% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 97/246	medium · avg 61%	▇ 3.6%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	61.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 128/246	medium · avg 60%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	50.3% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 18/246	easy · avg 83%	▇ 1.5%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	62.8% ✎	▁········▁▇█ beats 139/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	78.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 210/237	hard · avg 21%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	59.5% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 196/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▃▃▃▅▅▆█▂ #200 of 263 · 46% of its score · 14 tests

Trails laya (DecisionBench 1c5edc17), DM-JEPA 1.1, Sieve 2B 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	29.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 62/246	medium · avg 46%	▇▇▇ 8.1%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	51.4% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 61/246	easy · avg 70%	▇▇▇ 7.4%	sharp · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	74.6% ✎	▂▂▂▂▂▃▁▃▄▆█▆ beats 62/246	very easy · avg 90%	▇▇▇ 7.1%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	66.8% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 113/246	easy · avg 66%	▇▇ 6.2%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	88.5% ✎	▁▁▂▁▂▂▃▂▃▆█▅ beats 62/246	very easy · avg 96%	▇▇ 4.7%	sharp · maxed out · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	64.7% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 58/246	easy · avg 78%	▇ 3.4%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	34.8% ✎	▁··▄█▆▆▆▅▅▃▁ beats 91/246	medium · avg 45%	▇ 2.7%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	28.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 50/246	medium · avg 39%	▇ 2.4%	blunt · 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	71.8% ✎	▁▁▂█▅▄▃▁▁▁▁▁ beats 225/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	36.8% ✎	██▄▃▃▄▁▁···▁ beats 34/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	82.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 187/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	32.7% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 183/246	hard · avg 22%	▇ 0.9%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	19.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 166/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 139/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.8% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	39.9000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 98/247	avg 41.206 points	▇▇ 4.4%	blunt
Decision Index 0.4.1: private new domains (equated points)	14.1100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 50/247	avg 38.861 points	▇ 2.4%	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		= 44.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.1%	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]	70.8%	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

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