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JPT-9B Qwen3.5-9B LoRA

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JPT-9B Qwen3.5-9B LoRA is an open-weights decision model from kirp. Its published size is 9.65B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine jpt-9b; reported model JPT-9B Qwen3.5-9B LoRA. Type: LoRA; technique: autoregressive. Published checkpoint/base reference: 7114b0c3d9bea6b82dfa2d0691e8d5562cd26d4e. Implementation: https://github.com/tic-top/llm2jev. 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.

53.6±1.2#176 of 355 decision modelsfrom 56 benchmark results across 3 sources

$ how it compares

The decision models ranked either side of JPT-9B Qwen3.5-9B LoRA, out of 357 with a score, then more from kirp.

#	model	score	where	RAM
176	vLLM-SR Decision 2.0 Lux 9B vLLM Semantic Router	54±1	local	~20GB
177	JevAny-Gemma-4B (pointer) (JevBench mini) SimpleJev	54±2	source code
178	JPT-9B Qwen3.5-9B LoRA kirp	54±1	model files
179	Saif 4B Gyr Technology	54±1	model files
180	SemIf (DecisionBench 1f2dea3e) TheoLeeCJ	54±2	source code
	more from kirp
128	JPT-35B-A3B kirp	58±1	model files
204	JPT-4B Qwen3.5-4B LoRA kirp	50±1	model files
289	JPT-0.8B Qwen3.5-0.8B LoRA kirp	33±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #123 of 250 · 6.8% of its score · 6 tests

Beats Tern-35B-A3B, GEV-26B-Decide, Cerno 4B v1.1 here, though they rank higher overall. Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, 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: API-Bank (accuracy) submitted	78.7% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 112/236	easy · avg 70%	▇ 2.1%	sharp · at its level · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	94.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 128/246	very easy · avg 92%	▇ 1.8%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	43.2% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 119/243	medium · avg 37%	▇ 1.0%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	68.0% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 90/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	61.7% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 85/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.1% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #137 of 258 · 5.6% of its score · 7 tests

Beats Quyet-1.0-Large, Decider chat · Qwen3.6-27B (decision readout), Xor 1.2 here, though they rank higher overall. Trails vLLM-SR vela3-fast (Vela 3.0, 0.4B), crystal-0.8b, Kas 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) submitted	46.9% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 177/246	medium · avg 38%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	52.6% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 125/246	medium · avg 47%	▇ 1.9%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	66.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 86/246	easy · avg 74%	▇ 0.5%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	76.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 157/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	36.2% ✎	▁▁▁▁▁▁▃▂▃▆█▄ beats 19/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	65.4% ✎	▁·▁▁▁▁▁▁▃█▇█ beats 31/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	53.0% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #138 of 256 · 20% of its score · 9 tests

Beats Solar Decide, Winnow-12B, JoshuaSP diffgemma (decision readout) here, though they rank higher overall. Trails Ryotide Qwen v0.3.1 (decision readout), Sieve 2B v3, RSI-Jev v5.0 VL 3B 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	85.9% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 116/246	very easy · avg 85%	▇▇ 4.9%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	79.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 145/246	easy · avg 74%	▇▇ 4.8%	typical
Decision Index 0.4.1: ANLI (macro-F1) submitted	66.6% ✎	▁▂▃▅▅█▂····▁ beats 135/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	56.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 169/246	medium · avg 44%	▇ 2.0%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	22.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 130/246	hard · avg 22%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	82.2% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 183/246	easy · avg 71%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	64.4% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 117/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	76.2% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 137/246	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: FinEntity (macro-F1) submitted	93.2% ✎	▁···▁▁▁▁▃▆█▃ beats 192/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #136 of 247 · 8.1% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5, Cerno 4B v1.1 here, though they rank higher overall. Trails Crivo-68M, Crivo-150M v2, vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B) 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	62.1% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 115/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	59.7% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 91/246	medium · avg 60%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	86.1% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 111/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	57.5% ✎	▁········▁▇█ beats 73/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	4.7% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 70/237	hard · avg 21%	▇ 0.7%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.2% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 68/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #121 of 263 · 40% of its score · 14 tests

Beats OneJev1.6-4B, Winnow-12B (DecisionBench b6ac22b0), Cerno 4B v1.1 here, though they rank higher overall. Trails PurpleMIST-Flash-1.0 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	54.7% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 131/246	medium · avg 46%	▇▇▇▇ 9.0%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	77.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 140/246	easy · avg 70%	▇▇▇ 6.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	69.4% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 130/246	easy · avg 66%	▇▇ 5.6%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	94.7% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 138/246	very easy · avg 90%	▇▇ 3.8%	sharp · maxed out
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	48.9% ✎	▁··▄█▆▆▆▅▅▃▁ beats 137/246	medium · avg 45%	▇ 3.0%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	74.6% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 108/246	easy · avg 78%	▇ 2.8%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	41.3% ✎	▂▆▅▅▆█▆▃▁··▁ beats 125/246	medium · avg 39%	▇ 2.7%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	97.8% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 120/246	very easy · avg 96%	▇ 2.0%	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	23.6% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 97/246	hard · avg 22%	▇ 1.2%	at its level
Decision Index 0.4.1: MuSR (accuracy) submitted	54.8% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 64/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	55.6% ✎	██▄▃▃▄▁▁···▁ beats 132/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	66.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 110/246	easy · avg 71%	▇ 0.8%	at its level
Decision Index 0.4.1: ChessBench (accuracy) submitted	14.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 111/246	hard · avg 16%	▇ 0.5%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.2% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 119/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #42 of 79 · 12% of its score · 14 tests

Beats Surogate Rune 26B-A4B v3, Clef-omni, matilda-jev-v1.5 (27B) here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	69.0300 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 25/61	avg 63.423 points	▇ 1.3%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	33.7700 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 37/61	avg 22.797 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	79.2500 points ✎	▁·▁▁▁▁·▂▁▃▅█ beats 29/61	avg 66.987 points	▇ 1.1%	blunt
Decision Index Vision 0.4: private same skills (points)	58.0400 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 33/61	avg 48.067 points	▇ 1.1%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	23.1700 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 14/61	avg 28.443 points	▇ 1.0%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	65.0400 points ✎	▁·▂▂▁▃▃▅▅▃▂█ beats 40/61	avg 53.651 points	▇ 0.9%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	69.1700 points ✎	▂▁▁▁▁▃▁▅▅▆██ beats 25/61	avg 62.137 points	▇ 0.9%	blunt
Benchmark Heaven imagejevbench v0.3.0: intelligence (points)	44.2878 points ✎	▃·▃▃··▅█▅▅·▃ beats 8/12	avg 32.235 points	▇ 0.8%	blunt

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	93.4400 points ✎	▁·▁▂▁▁▃▁▂▂▅█ beats 33/61	avg 83.859 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted	18.4200 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 19/61	avg 19.676 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	52.9600 points ✎	▁···▁▂▂▂█▄▂▃ beats 25/61	avg 44.994 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	76.0400 points ✎	▁▁▁▁▂▁▁▁▄█▃▃ beats 38/61	avg 67.662 points	▇ 0.5%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	91.7800 points ✎	▁··▁▁▁▁▁▂▄█▁ beats 34/61	avg 85.184 points	▇ 0.4%	blunt
Benchmark Heaven imagejevbench v0.3.0: calibration (points)	73.1602 points ✎	▃···▃·▅█▅▃▃▅ beats 8/12	avg 68.584 points	▇ 0.3%	blunt

other tests2 not in a task · 7.1% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	42.9000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 115/247	avg 41.206 points	▇▇ 4.6%	blunt
Decision Index 0.4.1: private new domains (equated points)	45.8500 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 145/247	avg 38.861 points	▇ 2.5%	blunt

$ where to run it

Download model files ↗
Published model files verified. This is the revision recorded by the benchmark. 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/kirp ↗

$ how the score was worked out · Decision Index 0.4.1 88%, Decision Index Vision 0.4 10%, Benchmark Heaven (own decisio… 1%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 88%	CC BY 4.0
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇▇ 10%	CC BY 4.0
Benchmark Heaven (own decision evaluations)	2	▇ 1%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 53.6

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.1%	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]	53.0%	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