whatmodel.sh / decision / Intelif Qwen3-4B

Intelif Qwen3-4B

+ contribute

Intelif Qwen3-4B is an open-weights decision model from UserMoonlight. Its published size is 4.02B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine intelif-qwen3-4b; reported model Intelif Qwen3-4B. 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

· Weights licence ↗ · Parameter count ↗

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

42.9±1.1#250 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Intelif Qwen3-4B, out of 357 with a score.

#	model	score	where	RAM
250	QEV-0.8B ken-jo	44±4	model files
251	openvons Qwen3-4B (decision readout) genai-craft	43±1	source code
252	Intelif Qwen3-4B UserMoonlight	43±1	model files
253	Crivo-1B tardellirs	43±1	model files
254	vLLM-SR d3-lite (0.8B) vLLM Semantic Router	42±1	local	~4.5GB

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #155 of 250 · 8.8% of its score · 6 tests

Beats Trio-Spark DI (9B), Decider 35B-A3B, LiquidAI d1-3B 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	92.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 96/246	very easy · avg 92%	▇ 3.7%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	64.6% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 78/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	44.5% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 32/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	67.7% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 195/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	2.3% ✎	█▃▁▃▄▄▆▄▁▂▁▃ beats 53/243	medium · avg 37%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.8% ✎	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▁▁▁·▁▁▃▁▃▃█▅ #224 of 258 · 5.4% of its score · 7 tests

Trails Bosun v3.1 0.6B LoRA, Crivo-32M v2, Jev-Style 0.8B v3 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	40.5% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 101/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	29.1% ✎	▁▁▁▁▁▁▃▂▃▃█▅ beats 31/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	56.4% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 29/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	81.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 71/238	easy · avg 83%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 22/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	83.8% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 128/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	54.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #190 of 256 · 24% of its score · 9 tests

Beats Nari Decision 4B v3.2, Solar Decide Flash, TokenRhythm NeoHorse-Jev-4B here, though they rank higher overall. Trails DecisionTune 1.0, vera-spark, JEV FLAN-T5 Large public v2 (342M) 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	76.2% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 65/246	very easy · avg 85%	▇▇▇ 8.2%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	69.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 75/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	50.0% ✎	▁▂▃▅▅█▂····▁ beats 67/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	28.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 52/246	medium · avg 44%	▇ 1.7%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	56.2% ✎	▁▁▁▁▁▁▁▃▂▇▇█ beats 43/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	39.4% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 28/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	80.5% ✎	▁···▁▁▁▁▃▆█▃ beats 72/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	26.9% ✎	▁▁▁▁▁▁▁▃▁▃▆█ beats 26/246	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	19.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 102/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #171 of 247 · 8.1% of its score · 6 tests

Beats PurpleMIST-Flash-1.0, vLLM-SR Decision 2.0 Nox 4B, Sieve 9B here, though they rank higher overall. Trails Crivo-17M, Crivo-32M v2, Crivo-68M 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	54.0% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 67/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	52.8% ✎	▁·▁▃▃▂▅█▄▂▁▁ beats 43/246	medium · avg 60%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	74.5% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 76/246	easy · avg 83%	▇ 1.5%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	57.9% ✎	▁········▁▇█ beats 76/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	12.7% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 109/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	32.7% ✎	▁▃▄█▇▅▁▁▄▄▁▁ beats 9/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #180 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. Trails mini-jev Qwen3-4B (decision readout), Cam1 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	88.8% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 89/246	very easy · avg 90%	▇▇▇ 7.7%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	41.3% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 83/246	medium · avg 46%	▇▇▇ 7.6%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	64.5% ✎	▁▄▄▃▃▃▅▇▅█▇▁ beats 80/246	easy · avg 70%	▇▇▇ 7.4%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	56.4% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 74/246	easy · avg 66%	▇▇ 6.1%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	96.1% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 91/246	very easy · avg 96%	▇▇ 5.4%	sharp · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	65.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 59/246	easy · avg 78%	▇ 3.4%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	34.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 89/246	medium · avg 45%	▇ 2.5%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	32.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 70/246	medium · avg 39%	▇ 2.3%	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	60.5% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 137/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	40.4% ✎	██▄▃▃▄▁▁···▁ beats 61/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	57.6% ✎	▁███▆▅▃▃▁▁▁▁ beats 57/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	16.6% ✎	▁▁▁▁▁▁▁▃▅█▂▁ beats 61/246	hard · avg 22%	▇ 0.8%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	15.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 112/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 90/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	35.2800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 78/247	avg 41.206 points	▇▇ 4.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	25.4100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 85/247	avg 38.861 points	▇ 2.3%	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/UserMoonlight ↗

$ 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		= 42.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.8%	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]	54.9%	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