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KnowLine 31B Gen1

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KnowLine 31B Gen1 is an open-weights decision model from PelaAI, released 24 October 2026. Its published size is 31.27B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine knowline-31b-gen1; reported model KnowLine 31B 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

73.2±1.5#5 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of KnowLine 31B Gen1, out of 357 with a score, then more from PelaAI.

#	model	score	where	released
3	Sieve 31B v3 Sthānika AI	74±2	model files	2026-10-27
4	Fastino GLiDE 1.2 Fastino	73±1	model files	2026-10-22
5	KnowLine 31B Gen1 PelaAI	73±2	model files	2026-10-24
6	Ainvest-Decision-27B v1.0 Ainvest-World	73±2	model files	2026-10-27
7	StartLux-Decision v1.1 27B StartLux	73±1	model files
	more from PelaAI
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
52	KnowLine 9B Gen1 PelaAI	66±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #29 of 250 · 4.9% of its score · 6 tests

Beats Jeffan-31b-1710, Fastino GLiDE 1.2 here, though they rank higher overall. Trails Solomon v1.1, 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: API-Bank (accuracy) submitted	89.0% ✎	▁▁▁▁▁▁▁▂▃▂█▃ beats 224/236	easy · avg 70%	▇ 1.4%	sharp · maxed out · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	69.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 225/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	91.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 232/246	easy · avg 72%	▇ 0.9%	noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	81.8% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 198/243	medium · avg 37%	▇ 0.8%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.8% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 214/246	very easy · avg 92%	▇ 0.6%	sharp · maxed out · noisy
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▁▁▁·▁▁▁▁▃▃█▅ #27 of 258 · 8.5% of its score · 7 tests

Trails JEV-35B, StartLux-Decision v1.1 4B, Torchcast Decision 27B 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	50.4% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 240/246	medium · avg 38%	▇ 3.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	60.9% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 220/246	medium · avg 47%	▇ 3.1%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	85.8% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 190/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	98.0% ✎	█▅▅▄▃▂▁▁▃▁·▁ beats 242/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	82.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 118/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	93.2% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 179/238	easy · avg 83%	▇ 0.2%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	55.8% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #33 of 256 · 21% of its score · 9 tests

Trails Clef-flash, Clef-omni, vLLM-SR d3-flash (9B) 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	80.3% ✎	▁▂▃▅▅█▃····▁ beats 239/246	medium · avg 60%	▇▇ 5.4%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	87.7% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 243/246	easy · avg 74%	▇▇ 5.0%	typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	68.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 225/246	medium · avg 44%	▇ 3.0%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	47.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 218/246	hard · avg 22%	▇ 2.2%	at its level · noisy
Decision Index 0.4.1: HellaSwag (accuracy) submitted	96.3% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 212/246	very easy · avg 85%	▇ 2.0%	sharp · maxed out
Decision Index 0.4.1: VAST (macro-F1) submitted	82.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 242/246	medium · avg 62%	▇ 1.1%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	79.4% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 156/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	82.6% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 207/246	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	93.0% ✎	▁···▁▁▁▁▃▆█▃ beats 189/246	easy · avg 84%	▇ 0.4%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▃▁▁ #19 of 247 · 11% of its score · 6 tests

Beats Jeffan-31b-1710 here, though they rank higher overall. Trails Senova-4B v2, AnyJev L0 · Gemma-4-31B (decision readout), RSI-Jev v6.1 VL 27B (effort auto) 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	84.9% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 242/246	medium · avg 61%	▇▇ 3.9%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	69.3% ✎	▁·▁▃▂▂▅█▄▃▁▁ beats 240/246	medium · avg 60%	▇ 2.7%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	69.2% ✎	▁········▁▇█ beats 236/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	74.4% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 198/237	hard · avg 21%	▇ 1.3%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	97.5% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 228/246	easy · avg 83%	▇ 0.7%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	55.4% ✎	▁▂▄█▇▅▁▃▄▄▁▁ beats 185/246	medium · avg 47%	▇ 0.5%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▃ #7 of 263 · 42% of its score · 14 tests

Beats Fastino GLiDE 1.2 here, though they rank higher overall. Trails Jev 1.13, Perplexity Decider v1.1 (27B), vLLM-SR d3-ultra (Decision 3.0, 27B) 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	76.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 242/246	medium · avg 46%	▇▇▇▇ 11%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	87.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 225/246	easy · avg 66%	▇▇ 5.4%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	89.7% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 238/246	easy · avg 70%	▇▇ 5.0%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	54.6% ✎	▂▆▅▅▆█▆▃▁··▁ beats 226/246	medium · avg 39%	▇▇ 4.8%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	92.6% ✎	▁··▄█▆▆▆▅▅▃▃ beats 246/246	medium · avg 45%	▇ 3.5%	sharp
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	39.3% ✎	▁▁▁▁▁▁▁▂▅█▃▁ beats 222/246	hard · avg 22%	▇ 2.7%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	94.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 225/246	easy · avg 78%	▇ 2.4%	typical
Decision Index 0.4.1: MuSR (accuracy) submitted	69.0% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 209/246	medium · avg 60%	▇ 1.6%	blunt · at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ChessBench (accuracy) submitted	31.6% ✎	▄▇▄▄▄▆▄█▄▃▁▁ beats 240/246	hard · avg 16%	▇ 1.3%	blunt
Decision Index 0.4.1: CRUXEval (accuracy) submitted	92.6% ✎	██▄▃▃▄▃▁···▁ beats 242/246	medium · avg 58%	▇ 1.2%	noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.9% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 239/246	very easy · avg 90%	▇ 1.1%	sharp · maxed out
Decision Index 0.4.1: CLadder (accuracy) submitted	89.4% ✎	▁███▆▅▃▃▁▁▁▁ beats 219/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.0% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 187/246	very easy · avg 96%	▇ 0.4%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	15.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 204/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 13% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	66.9400 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 245/247	avg 41.206 points	▇▇▇ 8.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	79.2400 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 247/247	avg 38.861 points	▇▇ 4.5%	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		= 73.2

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]	55.8%	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