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Standard One 3B SH (v4)

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Standard One 3B SH (v4) is an open-weights decision model from Standard Thinking. Its published size is 3.85B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine standard-one-3b-sh-v4; reported model Standard One 3B SH (v4). 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.

53.8±1.2#172 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Standard One 3B SH (v4), out of 357 with a score, then more from Standard Thinking.

#	model	score	where	RAM
172	Bespoke-Nimble-9B (DecisionBench 594dfdcf) Bespoke Labs	54±2	model files
173	JevAny-Qwen-4B (pointer) (JevBench mini) SimpleJev	54±2	source code
174	Standard One 3B SH (v4) Standard Thinking	54±1	model files
175	decider-4b v2.1 (JevBench mini) Mapika	54±2	source code
176	vLLM-SR Decision 2.0 Lux 9B vLLM Semantic Router	54±1	local	~20GB
	more from Standard Thinking
47	Standard One 35B SH (v1) Standard Thinking	66±1	model files
161	Standard One 8B SH (v4) Standard Thinking	55±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #82 of 250 · 7.6% of its score · 6 tests

Beats Sieve 27B v2, Jev 1.13, Span-02 (Gemma 4 26B-A4B) here, though they rank higher overall. Trails Jev-Omni, baselabs joey-1 (2B), Hopper 12B (trained) 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	88.0% ✎	▁▁▁▁▁▁▁▂▃▂█▃ beats 217/236	easy · avg 70%	▇ 2.3%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 164/246	very easy · avg 92%	▇ 2.1%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	100.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 229/243	medium · avg 37%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	87.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 190/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	65.9% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 158/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	78.3% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #73 of 258 · 6.4% 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 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	43.5% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 133/246	medium · avg 38%	▇ 2.3%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	56.9% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 179/246	medium · avg 47%	▇ 2.2%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	80.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 144/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	84.8% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 189/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	95.3% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 209/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	90.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 195/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	16.4% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #123 of 256 · 23% of its score · 9 tests

Beats garum (Gemma 4 31B), Shisa DE-2.1 (repeat), garas (Gemma 4 31B) here, though they rank higher overall. Trails vLLM-SR d3-nano (2B), Decider 4B, jiwo 4B v2 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	90.4% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 130/246	very easy · avg 85%	▇▇ 5.5%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	77.1% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 114/246	easy · avg 74%	▇▇ 5.4%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	62.7% ✎	▁▂▃▅▅█▂····▁ beats 114/246	medium · avg 60%	▇▇ 5.3%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	48.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 128/246	medium · avg 44%	▇ 2.3%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	40.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 201/246	hard · avg 22%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	85.6% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 236/246	easy · avg 71%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	61.6% ✎	▁▁▁▂▅▄▄▃▄▆█▄ beats 112/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	76.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 136/246	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	88.4% ✎	▁···▁▁▁▁▃▆█▃ beats 127/246	easy · avg 84%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #79 of 247 · 9.2% of its score · 6 tests

Beats Jev 1.13, Quyet-1.0-Large, jev-brain · Gemma-4-31B (decision readout) here, though they rank higher overall. Trails Amber 0.4B, Crivo-1B, Kas 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	60.8% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 106/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	59.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 85/246	medium · avg 60%	▇ 1.9%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	92.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 170/246	easy · avg 83%	▇ 1.2%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	60.6% ✎	▁········▁▇█ beats 108/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	69.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 194/237	hard · avg 21%	▇ 0.8%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	59.7% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 201/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #174 of 263 · 45% of its score · 14 tests

Trails openvons Qwen3-4B (decision readout), Jevstral 8B, Jobe Qwen3.5-4B (decision readout) 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	41.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 82/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	68.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 91/246	easy · avg 70%	▇▇▇ 7.1%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	76.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 170/246	easy · avg 66%	▇▇▇ 6.4%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	87.1% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 81/246	very easy · avg 90%	▇▇ 4.3%	sharp · maxed out
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	51.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 139/246	medium · avg 45%	▇ 3.4%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	81.3% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 132/246	easy · avg 78%	▇ 3.2%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	29.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 55/246	medium · avg 39%	▇ 3.0%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	94.8% ✎	▁▁▂▁▂▂▂▃▃▆█▅ beats 81/246	very easy · avg 96%	▇ 2.2%	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	33.3% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 186/246	hard · avg 22%	▇ 1.3%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	70.0% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 214/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	47.0% ✎	██▄▃▃▄▁▁···▁ beats 96/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	88.3% ✎	▁███▆▅▃▃▁▁▁▁ beats 214/246	easy · avg 71%	▇ 1.0%	at its level
Decision Index 0.4.1: ChessBench (accuracy) submitted	21.3% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 178/246	hard · avg 16%	▇ 0.6%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	9.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 24/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.0% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	49.3100 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 141/247	avg 41.206 points	▇▇ 5.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	25.5100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 86/247	avg 38.861 points	▇ 2.9%	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/StandardThinking ↗

$ 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		= 53.8

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	78.3%	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]	16.4%	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

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