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Decider chat · Gemma-4-31B (decision readout)

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Decider chat · Gemma-4-31B (decision readout) is a source-available decision implementation from Mapika. Its published size is 32.68B parameters.

Catalogue identity notes

Exact Decision Index tested engine decider-chat-gemma4-31b; reported model Decider chat · Gemma-4-31B. Type: inference technique; technique: autoregressive. Published checkpoint/base reference: google/gemma-4-31B-it. 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.

62.1±1.4#85 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Decider chat · Gemma-4-31B (decision readout), out of 357 with a score, then more from Mapika.

#	model	score	where	released
83	JEV-35B AutoTrust AI Lab	63±1	model files
84	SynACK Decide 26B-A4B v7 SkyPanther	62±1	model files
85	Decider chat · Gemma-4-31B (decision readout) Mapika	62±1	source code
86	Tern-35B-A3B matthewagi	62±1	model files
87	garum (Gemma 4 31B) plantwaterer	62±1	model files
	more from Mapika
43	Decider 31B (NVFP4) Mapika	66±1	model files	2026-10
110	decider-35b-a3b (DecisionBench d9783c58) Mapika	60±2	model files	2026-09-20
122	Decider chat · Qwen3.6-27B (decision readout) Mapika	59±1	source code

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #20 of 250 · 6.5% of its score · 6 tests

Beats Jeffan-31b-1710, Sieve 31B v3, Fastino GLiDE 1.2 here, though they rank higher overall. Trails Solomon v1.1, 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: API-Bank (accuracy) submitted	85.0% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 163/236	easy · avg 70%	▇ 2.0%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	98.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 235/246	very easy · avg 92%	▇ 1.2%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	62.5% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 151/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	63.6% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 111/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	76.9% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 122/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #121 of 258 · 7.2% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Quyet-1.0-Large here, though they rank higher overall. Trails vLLM-SR vela3-fast (Vela 3.0, 0.4B), crystal-0.8b, Kas 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	43.6% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 135/246	medium · avg 38%	▇ 2.9%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	53.1% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 133/246	medium · avg 47%	▇ 2.6%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	76.4% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 129/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	87.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 202/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	91.2% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 143/238	easy · avg 83%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	79.1% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 87/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	3.1% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #114 of 256 · 22% of its score · 9 tests

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	73.2% ✎	▁▂▃▅▅█▂····▁ beats 177/246	medium · avg 60%	▇▇ 5.5%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	82.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 185/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	92.0% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 140/246	very easy · avg 85%	▇ 3.7%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	51.1% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 139/246	medium · avg 44%	▇ 2.6%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	18.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 100/246	hard · avg 22%	▇ 1.6%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	73.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 157/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	73.6% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 100/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	76.9% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 143/246	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	90.9% ✎	▁···▁▁▁▁▃▆█▃ beats 164/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #105 of 247 · 10% of its score · 6 tests

Beats Bobcat 1.3 (31B), Nace.AI Drex v2.0 (35B-A3B), decisio 0.6.0 (Gemma 4 31B) (decision readout) 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	73.9% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 179/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	63.8% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 191/246	medium · avg 60%	▇ 2.2%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	64.1% ✎	▁········▁▇█ beats 163/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	28.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 147/237	hard · avg 21%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	90.3% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 142/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	47.9% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 167/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #59 of 263 · 44% of its score · 14 tests

Beats OneJev1.6-27B, baselabs elephant-1 (9B), StartLux-Decision v1.1 9B 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	69.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 206/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	86.3% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 200/246	easy · avg 70%	▇▇▇ 6.4%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	76.2% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 168/246	easy · avg 66%	▇▇ 6.1%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	49.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 190/246	medium · avg 39%	▇ 3.7%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	71.0% ✎	▁··▄█▆▆▆▅▅▃▁ beats 190/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.7% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 150/246	easy · avg 78%	▇ 2.9%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.4% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 224/246	very easy · avg 90%	▇ 2.5%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	29.3% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 136/246	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	64.2% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 170/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	79.3% ✎	██▄▃▃▄▁▁···▁ beats 195/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.8% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 170/246	very easy · avg 96%	▇ 1.1%	sharp · maxed out · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	74.6% ✎	▁███▆▅▃▃▁▁▁▁ beats 153/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	22.3% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 194/246	hard · avg 16%	▇ 0.8%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	14.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 192/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 10% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	56.4800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 184/247	avg 41.206 points	▇▇ 6.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	69.3500 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 210/247	avg 38.861 points	▇ 3.4%	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		= 62.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.0%	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]	3.1%	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