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Decider chat · Qwen3.6-27B (decision readout)

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Decider chat · Qwen3.6-27B (decision readout) is a source-available decision implementation from Mapika. Its published size is 27.78B parameters.

Catalogue identity notes

Exact Decision Index tested engine decider-chat-qwen3.6-27b; reported model Decider chat · Qwen3.6-27B. Type: inference technique; technique: autoregressive. Published checkpoint/base reference: Qwen/Qwen3.6-27B. Implementation: https://github.com/Mapika/decider. Comparison entry; no current run command, API price or speed inferred from the benchmark.

Model information sources

· Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

58.8±1.3#120 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Decider chat · Qwen3.6-27B (decision readout), out of 357 with a score, then more from Mapika.

#	model	score	where	RAM	released
120	simplejev-qwen3.8-27b (DecisionBench 1d4bf0f2) featherless-ai	59±2	model files
121	Clef-omni Cloudflare	59±1	api $0.15/M input tokens +local	~87GB	2026-10
122	Decider chat · Qwen3.6-27B (decision readout) Mapika	59±1	source code
123	Xor 1.2 Juspay Technologies	59±1	model files		2026-09-28
124	jev-d3-46k tinnel123	59±4	model files
	more from Mapika
43	Decider 31B (NVFP4) Mapika	66±1	model files		2026-10
85	Decider chat · Gemma-4-31B (decision readout) Mapika	62±1	source code
110	decider-35b-a3b (DecisionBench d9783c58) Mapika	60±2	model files		2026-09-20

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #47 of 250 · 7.0% of its score · 6 tests

Beats Fastino GLiDE 1.2, vLLM-SR d3-ultra (Decision 3.0, 27B), AutoTrust-JEV-27B v1.1 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Bespoke Nimble 9B v3 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	79.7% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 116/236	easy · avg 70%	▇ 2.1%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.5% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 206/246	very easy · avg 92%	▇ 1.5%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	44.3% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 125/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	78.5% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 131/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	64.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 121/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.9% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #160 of 258 · 6.9% of its score · 7 tests

Trails DecisionTune 1.0, jiwo 0.8B v2, 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: BRIGHT (nDCG@10) submitted	46.7% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 174/246	medium · avg 38%	▇ 2.6%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	47.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 93/246	medium · avg 47%	▇ 2.4%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	68.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 93/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	67.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 118/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	85.1% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 79/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	75.1% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 62/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	17.6% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #54 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	74.6% ✎	▁▂▃▅▅█▂····▁ beats 192/246	medium · avg 60%	▇▇ 5.4%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	82.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 171/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	95.4% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 200/246	very easy · avg 85%	▇▇ 4.4%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	45.8% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 112/246	medium · avg 44%	▇ 2.5%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	24.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 140/246	hard · avg 22%	▇ 1.4%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	74.0% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 104/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	58.4% ✎	▁▁▁▂▅▄▄▃▄▆█▄ beats 101/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	75.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 129/246	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	81.8% ✎	▁···▁▁▁▁▃▆█▃ beats 77/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #126 of 247 · 10% of its score · 6 tests

Beats Bobcat 1.3 (31B), JEV-35B, OneJev1.6-4B 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	72.7% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 170/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	60.8% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 115/246	medium · avg 60%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	63.3% ✎	▁········▁▇█ beats 153/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	87.6% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 120/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: POP909-CL (accuracy) submitted	18.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 128/237	hard · avg 21%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.9% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 82/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #76 of 263 · 44% of its score · 14 tests

Beats StartLux-Decision v1.1 9B, Sieve 27B v2, StartLux-Decision v1.1 4B here, though they rank higher overall. Trails 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	62.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 169/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	85.2% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 192/246	easy · avg 70%	▇▇▇ 6.7%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	72.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 151/246	easy · avg 66%	▇▇▇ 6.3%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	41.5% ✎	▁··▄█▆▆▆▅▅▃▁ beats 116/246	medium · avg 45%	▇ 3.6%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	54.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 230/246	medium · avg 39%	▇ 3.4%	blunt · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.3% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 214/246	very easy · avg 90%	▇ 3.1%	sharp · maxed out
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.2% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 146/246	easy · avg 78%	▇ 3.0%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	34.8% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 203/246	hard · avg 22%	▇ 1.6%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.8% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 169/246	very easy · avg 96%	▇ 1.4%	sharp · maxed out · noisy
Decision Index 0.4.1: MuSR (accuracy) submitted	62.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 155/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	64.0% ✎	██▄▃▃▄▁▁···▁ beats 151/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	66.3% ✎	▁███▆▅▃▃▁▁▁▁ beats 103/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	17.6% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 145/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 91/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.9% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	51.7000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 152/247	avg 41.206 points	▇▇ 5.8%	blunt
Decision Index 0.4.1: private new domains (equated points)	59.1100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 182/247	avg 38.861 points	▇ 3.2%	blunt

$ where to run it

Implementation and setup instructions ↗
Published implementation and setup documentation verified. This entry describes a decision readout or evaluated configuration, not necessarily separate trained weights. Follow the referenced version and model settings; hardware compatibility has not been verified. Source · checked 2026-10-31.

Model repository and documentation: github.com/Mapika ↗

$ 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		= 58.8

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.9%	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]	17.6%	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