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KnowLine 9B Gen1

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KnowLine 9B Gen1 is an open-weights decision model from PelaAI. Its published size is 9.65B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine knowline-9b-gen1; reported model KnowLine 9B Gen1. 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.

65.5±1.4#52 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of KnowLine 9B Gen1, out of 357 with a score, then more from PelaAI.

#	model	score	where	released
50	Span-02 (Gemma 4 26B-A4B) Respan	66±1	api price unknown
51	RSI-Jev v6.1 VL 27B (effort auto) shgao	66±1	model files	2026-10-08
52	KnowLine 9B Gen1 PelaAI	66±1	model files
53	Herbert v0.5 leinenterprises	65±4	model files
54	StartLux-Decision v1.1 4B StartLux	65±1	model files
	more from PelaAI
5	KnowLine 31B Gen1 PelaAI	73±2	model files	2026-10-24
12	KnowLine 35B-A3B Gen1.5 PelaAI	71±2	model files	2026-10-22
22	KnowLine 26B-A4B Gen2.5 PelaAI	69±2	model files	2026-10-22

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #63 of 250 · 6.0% of its score · 6 tests

Beats OneShot 27B, mogan-decision-31B-it, Sieve 27B v2 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber Hybrid 4B (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	89.6% ✎	▁▁▁▁▁▁▁▂▃▂█▃ beats 230/236	easy · avg 70%	▇ 1.8%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	68.3% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 205/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	75.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 180/243	medium · avg 37%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.1% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 183/246	very easy · avg 92%	▇ 1.0%	sharp · maxed out · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	89.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 207/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	80.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #28 of 258 · 7.6% of its score · 7 tests

Beats Perplexity Decider v1.1 (27B), H2O Lightning 31B v1.1, AutoTrust-JEV-27B v1.1 here, though they rank higher overall. Trails JEV-35B, StartLux-Decision v1.1 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	49.4% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 223/246	medium · avg 38%	▇ 3.1%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	60.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 218/246	medium · avg 47%	▇ 2.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	86.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 200/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	96.4% ✎	█▅▅▄▃▂▁▃▁▁·▁ beats 235/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	82.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 117/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	90.2% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 131/238	easy · avg 83%	▇ 0.3%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	65.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #51 of 256 · 22% of its score · 9 tests

Beats Ainvest-Decision-27B v1.0, Turion Jev 31B, MISA AI 2.0 Decision Plus · oak 1.1 (31B) here, though they rank higher overall. Trails Decider 35B-A3B, Sieve 9B v2, Clef-flash here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ANLI (macro-F1) submitted	73.7% ✎	▁▂▃▅▅█▂····▁ beats 185/246	medium · avg 60%	▇▇ 5.5%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	84.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 200/246	easy · avg 74%	▇▇ 5.2%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	95.3% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 198/246	very easy · avg 85%	▇ 3.1%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	67.6% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 215/246	medium · avg 44%	▇ 2.8%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	49.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 222/246	hard · avg 22%	▇ 1.8%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.1% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 209/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	80.4% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 167/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	81.9% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 200/246	easy · avg 66%	▇ 0.7%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	90.8% ✎	▁···▁▁▁▁▃▆█▃ beats 161/246	easy · avg 84%	▇ 0.5%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #42 of 247 · 10% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), Nace.AI Drex Max v1 (27B) here, though they rank higher overall. Trails Kas 4B, baselabs joey-1 (2B), Xor 1.2 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	75.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 196/246	medium · avg 61%	▇▇ 4.1%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	65.1% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 206/246	medium · avg 60%	▇ 2.3%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	81.2% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 224/237	hard · avg 21%	▇ 1.3%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	68.8% ✎	▁········▁▇█ beats 234/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	95.6% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 205/246	easy · avg 83%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	60.8% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 210/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #75 of 263 · 43% of its score · 14 tests

Beats StartLux-Decision v1.1 9B, Sieve 27B v2 here, though they rank higher overall. Trails Solar Decide, Clef-flash, Clef-omni 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	65.1% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 180/246	medium · avg 46%	▇▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	84.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 177/246	easy · avg 70%	▇▇ 6.0%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	79.4% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 188/246	easy · avg 66%	▇▇ 6.0%	typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	48.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 181/246	medium · avg 39%	▇▇ 4.0%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	74.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 200/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	89.2% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 195/246	easy · avg 78%	▇ 2.8%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	35.5% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 209/246	hard · avg 22%	▇ 2.1%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.2% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 166/246	very easy · avg 90%	▇ 1.9%	sharp · maxed out

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	64.1% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 168/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	69.7% ✎	██▄▃▃▄▁▁···▁ beats 169/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	83.8% ✎	▁███▆▅▃▃▁▁▁▁ beats 195/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	23.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 205/246	hard · avg 16%	▇ 1.0%	blunt
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.9% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 174/246	very easy · avg 96%	▇ 0.8%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	13.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 159/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 10% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	60.4800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 209/247	avg 41.206 points	▇▇▇ 6.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	55.3800 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 172/247	avg 38.861 points	▇ 3.7%	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/PelaAI ↗

$ 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		= 65.5

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	80.0%	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]	65.2%	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