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CoCo-Decision-4B 2.4

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CoCo-Decision-4B 2.4 is an open-weights decision model from Corners, released 16 October 2026. Its published size is 4.21B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine coco-decision-2.4-4b; reported model CoCo-Decision-4B 2.4. 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

56.5±1.3#142 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of CoCo-Decision-4B 2.4, out of 357 with a score.

#	model	score	where	RAM	released
142	matilda-jev-v1.5 (27B) Maincode	57±4	model files		2026-10-09
143	Jebadiah 9B v2.1 (T1e) frontier-infra	57±1	local	~25GB	2026-10
144	CoCo-Decision-4B 2.4 Corners	57±1	model files		2026-10-16
145	Amber Hybrid 4B (decision readout) MLukauskas	57±1	model files
146	Solar Decide Upstage	57±1	api price unknown		2026-09-22

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #69 of 250 · 7.3% of its score · 6 tests

Beats Sieve 27B v2, Darwin-27B-ZTC, allec-oavg (Gemma 4 31B) here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber 4B 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 159/236	easy · avg 70%	▇ 2.2%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 178/246	very easy · avg 92%	▇ 1.8%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	70.5% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 170/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	89.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 206/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	51.9% ✎	▁▁▁▁▁·▁▁▃▄█▁ beats 34/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	74.9% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #78 of 258 · 6.7% 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, Standard One 3B SH (v4), Standard One 8B SH (v4) 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	34.9% ✎	▁▁▁▁▁▁▁▂▃▄▇█ beats 72/246	medium · avg 38%	▇ 2.5%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	56.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 176/246	medium · avg 47%	▇ 2.3%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	87.9% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 213/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	57.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 76/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	93.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 186/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	89.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 177/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	70.3% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #71 of 256 · 23% of its score · 9 tests

Beats Turion Jev 31B, AJev lm6q (Gemma 4 31B), oenogarum (Gemma 4 31B) here, though they rank higher overall. Trails Sieve 4B, Decider 35B-A3B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	76.7% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 112/246	easy · avg 74%	▇▇ 5.4%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	69.5% ✎	▁▂▃▅▅█▂····▁ beats 153/246	medium · avg 60%	▇▇ 5.3%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	94.4% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 184/246	very easy · avg 85%	▇▇ 4.9%	sharp
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	49.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 129/246	medium · avg 44%	▇ 2.4%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	35.9% ✎	▁··▂▃▃▅▇█▇▃▃ beats 186/246	hard · avg 22%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	84.0% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 208/246	easy · avg 71%	▇ 1.1%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.3% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 215/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	80.3% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 180/246	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	88.9% ✎	▁···▁▁▁▁▃▆█▃ beats 136/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #71 of 247 · 9.5% 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	70.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 156/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	66.2% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 217/246	medium · avg 60%	▇ 1.9%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	93.4% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 177/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	64.2% ✎	▁········▁▇█ beats 164/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.3% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 21/237	hard · avg 21%	▇ 0.9%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	47.4% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 162/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #126 of 263 · 45% of its score · 14 tests

Beats Winnow-12B (DecisionBench b6ac22b0), Cerno 4B v1.1 here, though they rank higher overall. Trails PurpleMIST-Flash-1.0, JPT-9B Qwen3.5-9B LoRA, vLLM-SR Decision 2.0 Lux 9B 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	54.8% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 133/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	75.2% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 122/246	easy · avg 70%	▇▇▇ 6.9%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	65.6% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 107/246	easy · avg 66%	▇▇▇ 6.3%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	94.4% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 131/246	very easy · avg 90%	▇ 3.6%	sharp · maxed out
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	51.8% ✎	▁··▄█▆▆▆▅▅▃▁ beats 141/246	medium · avg 45%	▇ 3.6%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	43.4% ✎	▂▆▅▅▆█▆▃▁··▁ beats 139/246	medium · avg 39%	▇ 3.3%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 142/246	easy · avg 78%	▇ 3.1%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 141/246	very easy · avg 96%	▇ 1.8%	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	32.7% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 182/246	hard · avg 22%	▇ 1.5%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	61.7% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 148/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	41.0% ✎	██▄▃▃▄▁▁···▁ beats 66/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	84.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 201/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	18.3% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 156/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	10.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 39/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	51.2100 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 150/247	avg 41.206 points	▇▇ 5.5%	blunt
Decision Index 0.4.1: private new domains (equated points)	36.9900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 110/247	avg 38.861 points	▇ 3.0%	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/corners-ai ↗

$ 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		= 56.5

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	74.9%	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]	70.3%	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

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data updated 2026-11-03 02:37 UTC · sources and licences · json