whatmodel.sh / decision / Hopper (G) 1.2 Qwen3.5-4B LoRA

Hopper (G) 1.2 Qwen3.5-4B LoRA

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Hopper (G) 1.2 Qwen3.5-4B LoRA is an open-weights decision model from HopitAI. Its published size is 4.66B parameters. Licence: other.

Catalogue identity notes

Exact Decision Index tested engine hopper-g-1.2; reported model Hopper (G) 1.2 Qwen3.5-4B LoRA. Type: LoRA; technique: autoregressive. Implementation: https://github.com/hopit-ai/hopper. 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.

49.2±1.2#213 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Hopper (G) 1.2 Qwen3.5-4B LoRA, out of 357 with a score, then more from HopitAI.

#	model	score	where	RAM	released
213	TinyJev-4B (JevBench mini) AnkitAI	50±2	source code
214	Nari Decision 4B v3.2 blackmallangcow	49±1	model files		2026-10-18
215	Hopper (G) 1.2 Qwen3.5-4B LoRA HopitAI	49±1	model files
216	vLLM-SR d3-nano (2B) vLLM Semantic Router	49±1	local	~8.2GB
217	Aurelis-2B Leptos Labs	49±1	model files
	more from HopitAI
187	Hopper 12B (trained) HopitAI	52±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #158 of 250 · 8.1% of its score · 6 tests

Beats Trio-Spark DI (9B), LiquidAI d1-3B, vLLM-SR Decision 2.0 Nox 4B here, though they rank higher overall. Trails JevK5 Lite, Gevva E2B, 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: BFCL (case exact accuracy) submitted	92.1% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 91/246	very easy · avg 92%	▇ 2.7%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	75.6% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 105/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	61.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 70/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	22.7% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 93/243	medium · avg 37%	▇ 0.9%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	62.0% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 87/246	medium · avg 60%	▇ 0.9%	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▁▁▁·▁▁▁▁▃▃█▅ #199 of 258 · 5.9% of its score · 7 tests

Trails Bosun v3.1 0.6B LoRA, Mola-68M, Bosun v3.1 1.7B LoRA 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	42.4% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 121/246	medium · avg 38%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	39.5% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 57/246	medium · avg 47%	▇ 2.0%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	64.5% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 77/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	61.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 90/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	79.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 64/238	easy · avg 83%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	72.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 52/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	64.4% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #145 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. Trails Decider 2B, Crivo-1B, Ryotide Qwen v0.3.1 (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	84.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 110/246	very easy · avg 85%	▇▇▇ 6.7%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	78.6% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 138/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	60.0% ✎	▁▂▃▅▅█▂····▁ beats 107/246	medium · avg 60%	▇▇ 5.0%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	43.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 107/246	medium · avg 44%	▇ 2.0%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	70.7% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 79/246	easy · avg 71%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	44.3% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 56/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	16.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 87/246	hard · avg 22%	▇ 0.9%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	69.6% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 93/246	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	83.2% ✎	▁···▁▁▁▁▃▆█▃ beats 87/246	easy · avg 84%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #147 of 247 · 8.8% 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) submitted	57.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 86/246	medium · avg 61%	▇▇ 3.8%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	60.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 109/246	medium · avg 60%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	83.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 101/246	easy · avg 83%	▇ 1.4%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	60.6% ✎	▁········▁▇█ beats 109/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	6.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 84/237	hard · avg 21%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.7% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 105/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #150 of 263 · 46% of its score · 14 tests

Beats Winnow-12B (DecisionBench b6ac22b0), StartLux-Decision v1.1 2B, Solomon v1.1 here, though they rank higher overall. Trails Ryotide Qwen v0.3.1 (decision readout), razorback16 diffgemma (decision readout), Solar Decide 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	48.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 107/246	medium · avg 46%	▇▇▇▇ 9.2%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	73.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 114/246	easy · avg 70%	▇▇▇ 7.4%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	64.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 101/246	easy · avg 66%	▇▇▇ 6.4%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	92.8% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 109/246	very easy · avg 90%	▇▇ 5.6%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	69.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 75/246	easy · avg 78%	▇ 3.3%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	97.4% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 107/246	very easy · avg 96%	▇ 3.3%	sharp · maxed out · noisy
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	29.0% ✎	▁··▄█▆▆▆▅▅▃▁ beats 75/246	medium · avg 45%	▇ 3.1%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	37.8% ✎	▂▆▅▅▆█▆▃▁··▁ beats 101/246	medium · avg 39%	▇ 2.7%	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	55.0% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 70/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	29.5% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 137/246	hard · avg 22%	▇ 1.1%	typical
Decision Index 0.4.1: CRUXEval (accuracy) submitted	47.2% ✎	██▄▃▃▄▁▁···▁ beats 98/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	63.0% ✎	▁███▆▅▃▃▁▁▁▁ beats 76/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: ChessBench (accuracy) submitted	13.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 102/246	hard · avg 16%	▇ 0.5%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	9.2% ✎	▁▁▃▃▆█▇▅▅▃▁▁ beats 14/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 7.3% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	41.8000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 108/247	avg 41.206 points	▇▇ 4.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	37.7100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 114/247	avg 38.861 points	▇ 2.6%	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 · submitted; independent execution unverified	42	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 49.2

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]	64.4%	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