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Hopper 12B (trained)

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Hopper 12B (trained) is an open-weights decision model from HopitAI. Its published size is 11.96B parameters. Licence: other.

Catalogue identity notes

Exact Decision Index tested engine hopper-12b-trained; reported model Hopper 12B (trained). Type: LoRA; 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.

52.4±1.2#185 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Hopper 12B (trained), out of 357 with a score, then more from HopitAI.

#	model	score	where	released
185	cua-s1-4b-0.2 (DecisionBench 16818868) cua-ai	53±2	model files
186	Bespoke-Nimble-9B (JevBench mini) Bespoke Labs	53±2	source code
187	Hopper 12B (trained) HopitAI	52±1	model files
188	Jebadiah 9B v2 (JevBench mini) Frontier Infra	52±2	source code
189	jiwo 4B v2 eljiwo	52±1	model files	2026-10-09
	more from HopitAI
215	Hopper (G) 1.2 Qwen3.5-4B LoRA HopitAI	49±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #71 of 250 · 7.8% 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) 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)	74.4% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 102/236	easy · avg 70%	▇ 2.4%	sharp · at its level · noisy
Decision Index 0.4.1: BFCL (case exact accuracy)	96.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 179/246	very easy · avg 92%	▇ 2.2%	sharp · maxed out · noisy
Decision Index 0.4.1: When2Call (accuracy)	71.5% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 100/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy)	31.8% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 108/243	medium · avg 37%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10)	65.6% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 150/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective))	79.3% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #159 of 258 · 6.3% of its score · 7 tests

Beats Decider chat · Qwen3.6-27B (decision readout), Solar Decide, decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout) here, though they rank higher overall. 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)	42.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 118/246	medium · avg 38%	▇ 2.2%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1)	48.3% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 98/246	medium · avg 47%	▇ 2.1%	at its level
Decision Index 0.4.1: HoVer (accuracy)	71.5% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 107/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy)	70.9% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 133/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1)	86.1% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 85/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1)	72.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 51/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1)	15.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #171 of 256 · 23% of its score · 9 tests

Trails DecisionTune 1.0, Decider 2B, vLLM-SR d3-lite (0.8B) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy)	80.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 82/246	very easy · avg 85%	▇▇ 5.9%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1)	77.6% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 123/246	easy · avg 74%	▇▇ 5.4%	typical
Decision Index 0.4.1: ANLI (macro-F1)	66.0% ✎	▁▂▃▅▅█▂····▁ beats 131/246	medium · avg 60%	▇▇ 5.2%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English)	48.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 127/246	medium · avg 44%	▇ 2.2%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1)	74.8% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 114/246	easy · avg 71%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ACOS (per-review F1)	21.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 116/246	hard · avg 22%	▇ 1.0%	noisy
Decision Index 0.4.1: VAST (macro-F1)	67.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 123/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class)	74.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 125/246	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)	91.8% ✎	▁···▁▁▁▁▃▆█▃ beats 176/246	easy · avg 84%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #148 of 247 · 9.1% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5, Jegue 0.1 (9B) here, though they rank higher overall. Trails Crivo-32M v2, Crivo-68M, Crivo-150M v2 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)	65.0% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 128/246	medium · avg 61%	▇▇ 3.9%	at its level
Decision Index 0.4.1: Humicroedit (accuracy)	61.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 125/246	medium · avg 60%	▇ 1.8%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy)	82.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 99/246	easy · avg 83%	▇ 1.3%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy)	61.6% ✎	▁········▁▇█ beats 121/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy)	15.9% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 124/237	hard · avg 21%	▇ 0.7%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy)	44.1% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 121/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #153 of 263 · 45% of its score · 14 tests

Beats StartLux-Decision v1.1 2B, Solomon v1.1, Standard One 3B SH (v4) here, though they rank higher overall. Trails Ryotide Qwen v0.3.1 (decision readout), Interfaze lev Qwen3.5-4B LoRA, razorback16 diffgemma (decision readout) 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)	53.5% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 128/246	medium · avg 46%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy)	73.8% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 112/246	easy · avg 70%	▇▇▇ 7.2%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy)	69.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 126/246	easy · avg 66%	▇▇▇ 6.4%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy)	91.3% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 99/246	very easy · avg 90%	▇▇ 4.6%	sharp
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice))	54.2% ✎	▁··▄█▆▆▆▅▅▃▁ beats 145/246	medium · avg 45%	▇ 3.3%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy)	74.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 102/246	easy · avg 78%	▇ 3.2%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy)	38.3% ✎	▂▆▅▅▆█▆▃▁··▁ beats 103/246	medium · avg 39%	▇ 2.9%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy)	94.8% ✎	▁▁▂▁▂▂▂▃▃▆█▅ beats 82/246	very easy · avg 96%	▇ 2.5%	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)	24.5% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 102/246	hard · avg 22%	▇ 1.2%	typical
Decision Index 0.4.1: MuSR (accuracy)	61.0% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 142/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy)	58.1% ✎	██▄▃▃▄▁▁···▁ beats 137/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy)	64.0% ✎	▁███▆▅▃▃▁▁▁▁ beats 90/246	easy · avg 71%	▇ 1.0%	at its level
Decision Index 0.4.1: ChessBench (accuracy)	17.2% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 134/246	hard · avg 16%	▇ 0.6%	blunt
Decision Index 0.4.1: HLE (accuracy)	12.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 103/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 7.8% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	46.4600 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 127/247	avg 41.206 points	▇▇ 5.0%	blunt
Decision Index 0.4.1: private new domains (equated points)	44.7000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 143/247	avg 38.861 points	▇ 2.8%	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/HopitAI ↗

$ 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	42	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 52.4

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.3%	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]	15.9%	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