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Qwen Decision 27B noncausal LoRA

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Qwen Decision 27B noncausal LoRA is an open-weights decision model from jsaurabh. Its published size is 27.78B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine qwen-decision-27b-noncausal; reported model Qwen Decision 27B noncausal LoRA. 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.

61.4±1.3#95 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Qwen Decision 27B noncausal LoRA, out of 357 with a score.

#	model	score	where	released
93	imajev-4b (DecisionBench 712891d1) mohit67890	62±2	model files
94	GPT-6 Luna Decisions OpenAI	62±1	api price unknown	2026-10-06
95	Qwen Decision 27B noncausal LoRA jsaurabh	61±1	model files
96	Lumma-fev-27B FrontiersMind	61±1	model files
97	vLLM-SR Decision 2.0 Vega 27B vLLM Semantic Router	61±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #60 of 250 · 6.6% of its score · 6 tests

Beats OneShot 27B, mogan-decision-31B-it, Sieve 27B v2 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber Hybrid 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: API-Bank (accuracy) submitted	85.8% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 184/236	easy · avg 70%	▇ 2.0%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 190/246	very easy · avg 92%	▇ 1.3%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	77.3% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 186/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	68.1% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 201/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	81.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 150/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.8% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #56 of 258 · 7.2% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, d1.1 (hosted), oenogarum (Gemma 4 31B) 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	46.9% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 178/246	medium · avg 38%	▇ 2.8%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	58.6% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 197/246	medium · avg 47%	▇ 2.5%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	80.9% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 152/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	61.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 88/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	89.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 121/238	easy · avg 83%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	78.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 84/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	25.3% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #94 of 256 · 22% of its score · 9 tests

Beats Turion Jev 31B, FlexDM · Gemma-4-31B (decision readout), jev-brain · Gemma-4-31B (decision readout) here, though they rank higher overall. Trails Decider 4B, jiwo 4B v2, Sieve 4B 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	69.9% ✎	▁▂▃▅▅█▂····▁ beats 156/246	medium · avg 60%	▇▇ 5.5%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	82.5% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 182/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	93.3% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 160/246	very easy · avg 85%	▇▇ 3.8%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	70.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 234/246	medium · avg 44%	▇ 2.6%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	17.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 94/246	hard · avg 22%	▇ 1.5%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	74.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 164/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	74.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 110/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	81.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 194/246	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	88.0% ✎	▁···▁▁▁▁▃▆█▃ beats 123/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #94 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	70.3% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 152/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	59.1% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 84/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	65.5% ✎	▁········▁▇█ beats 191/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	51.9% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 167/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	91.0% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 156/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.8% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 60/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #72 of 263 · 44% of its score · 14 tests

Beats StartLux-Decision v1.1 9B, Sieve 27B v2, RSI-Jev v6.1 VL 27B (effort auto) here, though they rank higher overall. Trails Solar Decide, Clef-flash, Clef-omni 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	64.8% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 176/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	85.1% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 189/246	easy · avg 70%	▇▇▇ 6.4%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	77.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 171/246	easy · avg 66%	▇▇ 6.2%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	55.5% ✎	▁··▄█▆▆▆▅▅▃▁ beats 150/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	51.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 206/246	medium · avg 39%	▇ 3.7%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	85.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 160/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.1% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 203/246	very easy · avg 90%	▇ 2.6%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	20.2% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 75/246	hard · avg 22%	▇ 1.8%	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	66.5% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 195/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	77.2% ✎	██▄▃▃▄▁▁···▁ beats 187/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.0% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 190/246	very easy · avg 96%	▇ 1.1%	sharp · maxed out · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	73.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 150/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	18.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 151/246	hard · avg 16%	▇ 0.8%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	10.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 47/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 9.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	57.3200 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 189/247	avg 41.206 points	▇▇ 6.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	66.8200 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 206/247	avg 38.861 points	▇ 3.4%	blunt

$ where to run it

Download model files ↗
Published model files verified. Includes adapters or readout weights; follow the model documentation for the required base model. 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/jsaurabh ↗

$ 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		= 61.4

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.8%	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]	25.3%	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