Decider 2B

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Decider 2B is an open-weights decision model from Mapika. Its published size is 2.27B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine decider-2b-fp8-http; reported model Decider 2B. Type: full fine-tune; technique: autoregressive. Published checkpoint/base reference: Mapika/decider-2b. 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.

40.8±1.1#262 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Decider 2B, out of 357 with a score, then more from Mapika.

#	model	score	where	RAM	released
262	open-jev (pngwn) pngwn	41±1	model files
263	Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326) llm-semantic-router	41±1	local	~5.8GB
264	Decider 2B Mapika	41±1	model files
265	FLock this-that 1.2 FLock.io	40±1	model files
266	jdi-ptr14-0.8b AnamK	40±1	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▁▃▁▁▁▂▃▄▆██▆ #197 of 250 · 9.0% of its score · 6 tests

Beats Cam1, mini-jev Qwen3-4B (decision readout) here, though they rank higher overall. Trails JevK5 Lite, Mola-68M, Dinah-1 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	82.9% ✎	▁▂▁▁▁▂▃▄▅▆█▁ beats 52/246	very easy · avg 92%	▇▇ 4.1%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	31.7% ✎	▁▁▁▁▁▁▃▂▃▂█▂ beats 24/236	easy · avg 70%	▇ 2.4%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	54.7% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 55/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	63.1% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 105/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	3.4% ✎	█▁▃▃▄▄▆▄▁▂▁▃ beats 56/243	medium · avg 37%	▇ 0.5%	sharp · noisy
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▁▁▁·▁▁▁▃▃▃█▅ #213 of 258 · 5.2% of its score · 7 tests

Beats openvons Qwen3-4B (decision readout), Intelif Qwen3-4B, mini-jev Qwen3-4B (decision readout) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Crivo-32M v2, Mola-68M 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	37.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 81/246	medium · avg 38%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	34.7% ✎	▁▁▁▁▁▁▂▃▃▃█▅ beats 45/246	medium · avg 47%	▇ 1.6%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	59.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 44/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	73.7% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 48/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 25/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	72.8% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 53/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	48.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #140 of 256 · 24% of its score · 9 tests

Beats Solar Decide, JoshuaSP diffgemma (decision readout), PurpleMIST-Flash-1.0 here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	85.8% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 115/246	very easy · avg 85%	▇▇▇ 8.7%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	65.5% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 60/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	49.4% ✎	▁▂▃▅▅█▂····▁ beats 64/246	medium · avg 60%	▇▇ 4.5%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	22.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 28/246	medium · avg 44%	▇ 1.6%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	63.4% ✎	▁▁▁▁▁▁▁▂▃▇▇█ beats 54/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	51.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 79/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	76.1% ✎	▁···▁▁▁▁▃▆█▃ beats 60/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	28.3% ✎	▁▁▁▁▁▁▁▃▁▃▆█ beats 27/246	easy · avg 66%	▇ 0.7%	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	7.9% ✎	▁··▂▃▃▅▇█▇▃▃ beats 41/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #189 of 247 · 7.9% of its score · 6 tests

Beats Kev 9B v2, vLLM-SR d3-nano (2B), Valen-4B here, though they rank higher overall. Trails Qwen-2.5-1B-RLCD (decision readout), Bekko System One v0 68M, Crivo-17M 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	44.7% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 46/246	medium · avg 61%	▇ 3.4%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	64.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 58/246	easy · avg 83%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	59.9% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 94/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	57.0% ✎	▁········▁▇█ beats 68/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	0.3% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 12/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.2% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 97/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #184 of 263 · 47% of its score · 14 tests

Beats baselabs joey-1 (2B), Aurelis-2B, StartLux-Decision v1.1 0.8B here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	85.2% ✎	▂▂▂▂▂▂▃▃▄▆█▆ beats 76/246	very easy · avg 90%	▇▇▇ 8.4%	sharp
Decision Index 0.4.1: MMLU (accuracy) submitted	61.9% ✎	▁▄▄▃▃▃▅▇▅█▇▁ beats 77/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	37.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 78/246	medium · avg 46%	▇▇▇ 7.1%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	93.8% ✎	▁▁▂▁▂▂▂▃▃▆█▅ beats 77/246	very easy · avg 96%	▇▇▇ 6.3%	sharp · noisy
Decision Index 0.4.1: BBH (accuracy) submitted	51.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 64/246	easy · avg 66%	▇▇ 6.0%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	67.7% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 69/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	23.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 50/246	medium · avg 45%	▇ 2.3%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	36.2% ✎	▂▆▅▅▆█▆▃▁··▁ beats 89/246	medium · avg 39%	▇ 2.2%	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	54.9% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 67/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	33.0% ✎	██▄▃▃▄▁▁···▁ beats 13/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	57.3% ✎	▁███▆▅▃▃▁▁▁▁ beats 55/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	24.7% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 104/246	hard · avg 22%	▇ 0.7%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	9.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 56/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 110/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.3% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	27.7500 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 60/247	avg 41.206 points	▇▇ 4.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	17.5100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 67/247	avg 38.861 points	▇ 2.2%	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/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		= 40.8

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]	48.9%	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