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Saina Helm 2 Omni (0.8B)

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Saina Helm 2 Omni (0.8B) is an open-weights decision model from Saina. Its published size is 0.85B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine saina-helm-2-omni; reported model Saina Helm 2 Omni (0.8B). Type: LoRA + head; 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.

38.9±1.0#267 of 355 decision modelsfrom 54 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of Saina Helm 2 Omni (0.8B), out of 357 with a score.

#	model	score	where	released
267	Saina Helm 2.0 v2 Saina	39±1	model files
268	Valen-2B Valen	39±1	model files
269	Saina Helm 2 Omni (0.8B) Saina	39±1	model files
270	EXAONE-4.0-1.2B-JEV v0.3 carrtesy	39±1	model files	2026-10-04
271	Von 1.3 (JevBench mini) wfzyx	39±2	source code

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #161 of 250 · 8.4% of its score · 6 tests

Beats Trio-Spark DI (9B), LiquidAI d1-3B, vLLM-SR Decision 2.0 Nox 4B here, though they rank higher overall. 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: BFCL (case exact accuracy) submitted	91.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 88/246	very easy · avg 92%	▇▇ 4.1%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	76.8% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 107/236	easy · avg 70%	▇ 2.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	80.5% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 144/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	56.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 45/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 14/243	medium · avg 37%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	76.5% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #147 of 258 · 4.7% 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 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	51.0% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 110/246	medium · avg 47%	▇ 1.4%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	30.1% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 49/246	medium · avg 38%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	76.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 128/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	89.9% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 125/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	51.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 51/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 154/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	41.0% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #218 of 256 · 22% of its score · 9 tests

Trails LiquidAI d1-omni-600M, DecisionTune 1.0, vera-spark 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	56.3% ✎	▂▄▃▂▄▇▃▇█▅▃▁ beats 38/246	very easy · avg 85%	▇▇▇ 8.2%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	61.6% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 45/246	easy · avg 74%	▇▇ 4.9%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	44.9% ✎	▁▂▃▅▅█▂····▁ beats 48/246	medium · avg 60%	▇▇ 4.0%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	30.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 61/246	medium · avg 44%	▇ 1.4%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	84.4% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 217/246	easy · avg 71%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	70.9% ✎	▁···▁▁▁▁▃▆█▃ beats 43/246	easy · avg 84%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	67.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 124/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	77.5% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 149/246	easy · avg 66%	▇ 0.6%	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	24.5% ✎	▁··▂▃▃▅▇█▇▃▃ beats 142/246	hard · avg 22%	▇ 0.5%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #180 of 247 · 7.1% of its score · 6 tests

Beats Sieve 9B, Kev 9B v2, vLLM-SR d3-nano (2B) here, though they rank higher overall. Trails Bekko System One v0 68M, Crivo-17M, Crivo-32M v2 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	54.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 70/246	medium · avg 61%	▇ 3.1%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	70.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 67/246	easy · avg 83%	▇ 1.5%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	60.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 107/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	58.2% ✎	▁········▁▇█ beats 80/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	5.3% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 76/237	hard · avg 21%	▇ 0.2%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	43.7% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 114/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▃▃▃▅▅▆█▂ #207 of 263 · 43% of its score · 14 tests

Beats Crivo-1B, vLLM-SR vela3-fast (Vela 3.0, 0.4B), Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326) here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), DM-JEPA 1.1, Strands Decider 2B (Hobson v21) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	71.3% ✎	▂▂▂▂▃▂▁▃▄▆█▆ beats 56/246	very easy · avg 90%	▇▇▇ 8.2%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	86.0% ✎	▁▁▂▁▂▃▂▂▃▆█▅ beats 57/246	very easy · avg 96%	▇▇▇ 6.6%	sharp · noisy
Decision Index 0.4.1: MMLU (accuracy) submitted	49.6% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 54/246	easy · avg 70%	▇▇▇ 6.6%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	25.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 53/246	medium · avg 46%	▇▇ 6.1%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	45.3% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 52/246	easy · avg 66%	▇▇ 5.3%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	61.4% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 49/246	easy · avg 78%	▇ 3.2%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	31.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 82/246	medium · avg 45%	▇ 2.0%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	29.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 54/246	medium · avg 39%	▇ 1.9%	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	49.6% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 28/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	69.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 123/246	easy · avg 71%	▇ 0.8%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	30.7% ✎	██▄▃▃▄▁▁···▁ beats 4/246	medium · avg 58%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	20.0% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 72/246	hard · avg 22%	▇ 0.6%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	18.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 160/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	14.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 171/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #76 of 79 · 8.3% of its score · 12 tests

Trails LiquidAI d1-omni-600M, Valen-0.8B, InternLM Intern-Decision Qwen3.5-2B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	50.8100 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 8/61	avg 63.423 points	▇ 1.1%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	7.1200 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 2/61	avg 22.797 points	▇ 1.0%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	50.7500 points ✎	▁·▁▁▃▁·▂▁▃▅█ beats 5/61	avg 66.987 points	▇ 0.9%	blunt
Decision Index Vision 0.4: private same skills (points)	34.1000 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 2/61	avg 48.067 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	11.4600 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 1/61	avg 28.443 points	▇ 0.8%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	43.1200 points ✎	▁·▂▂▃▃▃▅▅▃▂█ beats 7/61	avg 53.651 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	48.6200 points ✎	▂▁▁▃▁▃▁▅▅▆██ beats 6/61	avg 62.137 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	77.0500 points ✎	▁·▁▂▃▁▃▁▂▂▅█ beats 8/61	avg 83.859 points	▇ 0.5%	blunt

4 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted	16.4400 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 14/61	avg 19.676 points	▇ 0.5%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	32.9800 points ✎	▁···▁▃▂▂█▄▂▃ beats 5/61	avg 44.994 points	▇ 0.5%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	56.9400 points ✎	▁▁▃▁▂▁▁▁▄█▃▃ beats 4/61	avg 67.662 points	▇ 0.4%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	75.4200 points ✎	▁··▁▃▁▁▁▂▄█▁ beats 3/61	avg 85.184 points	▇ 0.3%	blunt

other tests2 not in a task · 5.6% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	34.5700 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 76/247	avg 41.206 points	▇ 3.6%	blunt
Decision Index 0.4.1: private new domains (equated points)	14.4900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 54/247	avg 38.861 points	▇ 2.0%	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/run-saina ↗

$ how the score was worked out · Decision Index 0.4.1 91%, Decision Index Vision 0.4 8%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 91%	CC BY 4.0
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇ 8%	CC BY 4.0
prior · pull toward the middle		▇ 0%
weighted average		= 38.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	76.5%	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]	41.0%	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