whatmodel.sh / decision / KnowLine 26B-A4B Gen2.5

KnowLine 26B-A4B Gen2.5 is an open-weights decision model from PelaAI, released 22 October 2026. Its published size is 25.81B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine knowline-26b-a4b-gen2.5; reported model KnowLine 26B-A4B Gen2.5. 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.

69.2±1.5#22 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of KnowLine 26B-A4B Gen2.5, out of 357 with a score, then more from PelaAI.

#modelscorewhereRAMreleased
20vera-large scar-ai70±2model files
21d1-ultra Liquid AI69±2api price unknown2026-10-15
22KnowLine 26B-A4B Gen2.5 PelaAI69±2model files2026-10-22
23OneJev1.6-27B OmniJev69±2model files2026-10-17
24baselabs elephant-1 (9B) baselabs69±1model files2026-10-21
more from PelaAI
5KnowLine 31B Gen1 PelaAI73±2model files2026-10-24
12KnowLine 35B-A3B Gen1.5 PelaAI71±2model files2026-10-22
52KnowLine 9B Gen1 PelaAI66±1model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #9 of 250 · 5.4% of its score · 6 tests

Beats Jeffan-31b-1710, Sieve 31B v3, Fastino GLiDE 1.2 here, though they rank higher overall. Trails Clef-flash, Clef-omni, Clef here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: API-Bank (accuracy) submitted90.8% ✎▁▁▁▁▁▁▁▂▃▂█▃ beats 234/236easy · avg 70%▇ 1.6%sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted69.6% ✎▁▁▁▁▁·▁▁▁▄█▁ beats 230/246medium · avg 60%▇ 1.2%blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted71.6% ✎█▁▁▃▄▄▆▄▁▂▁▃ beats 174/243medium · avg 37%▇ 0.9%sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted90.7% ✎▁▁▁▂▃▅▅▆█▇█▃ beats 226/246easy · avg 72%▇ 0.9%noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted98.2% ✎▁▂▁▁▁▂▂▄▅▆█▃ beats 238/246very easy · avg 92%▇ 0.8%sharp · maxed out · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted79.9% ✎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▁▁▁·▁▁▁▁▃▃█▅ #26 of 258 · 8.1% of its score · 7 tests

Beats KnowLine 31B Gen1, Perplexity Decider v1.1 (27B), H2O Lightning 31B v1.1 here, though they rank higher overall. Trails JEV-35B, StartLux-Decision v1.1 4B, Torchcast Decision 27B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted50.2% ✎▁▁▁▁▁▁▁▂▂▄▇█ beats 237/246medium · avg 38%▇ 3.4%blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted61.1% ✎▁▁▁▁▁▁▂▂▃▃█▅ beats 222/246medium · avg 47%▇ 2.9%at its level
Decision Index 0.4.1: HoVer (accuracy) submitted86.1% ✎▆▆▇▅▄▄▃▇▄█▆▄ beats 193/246easy · avg 74%▇ 0.6%blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted90.8% ✎█▅▅▄▃▃▁▁▁▁·▁ beats 217/245easy · avg 70%▇ 0.6%noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted82.8% ✎▁·▁▁▁▁▁▁▂█▇█ beats 116/238easy · avg 79%▇ 0.3%noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted93.0% ✎▁▁▁▁▁▁▁▂▃▆█▄ beats 175/238easy · avg 83%▇ 0.3%sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted68.3% ✎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▂▂▂▃▂▅▆▃█▆▄▃ #49 of 256 · 21% 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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ANLI (macro-F1) submitted76.0% ✎▁▂▃▅▅█▂····▁ beats 205/246medium · avg 60%▇▇ 5.5%typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted84.3% ✎▁▁▁▂▂▃▃▄▇▇█▄ beats 207/246easy · avg 74%▇▇ 5.1%typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted71.4% ✎▁·▁·▁▁▂▄▅█▇▄ beats 238/246medium · avg 44%▇ 2.9%at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted95.4% ✎▂▄▂▂▄▇▃▇█▅▃▁ beats 199/246very easy · avg 85%▇ 2.5%sharp · maxed out
Decision Index 0.4.1: ACOS (per-review F1) submitted48.2% ✎▁··▂▃▃▅▇█▇▃▃ beats 219/246hard · avg 22%▇ 2.0%at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted79.3% ✎▁▁▁▂▅▄▄▂▄▆█▄ beats 214/246medium · avg 62%▇ 1.1%typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted81.9% ✎▁▁▁▁▁▁▁▂▂▇▇█ beats 180/246easy · avg 71%▇ 1.0%noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted84.7% ✎▁▁▁▁▁▁▁▁▁▃▆█ beats 230/246easy · avg 66%▇ 0.7%noisy
1 more test
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: FinEntity (macro-F1) submitted92.7% ✎▁···▁▁▁▁▃▆█▃ beats 185/246easy · avg 84%▇ 0.5%maxed out · noisy
arts & human taste▁▇▄▃▅▅█▅▄▃▁▁ #20 of 247 · 10% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), WeMM-JEV-27B 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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: New Yorker (accuracy) submitted79.9% ✎▁▁▂▃▃▃▇▅█▅▃▁ beats 219/246medium · avg 61%▇▇ 4.0%typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted69.1% ✎▁·▁▃▂▂▅█▄▃▁▁ beats 238/246medium · avg 60%▇ 2.5%blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted68.2% ✎▁········▁▇█ beats 232/246medium · avg 60%▇ 1.4%blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted79.0% ✎▄▅▅▃▆▅▃▅▂▅▃█ beats 213/237hard · avg 21%▇ 1.4%sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted97.4% ✎▁█▄▄▅█▆▅▄▁▁▁ beats 227/246easy · avg 83%▇ 0.8%sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted59.7% ✎▁▂▄█▇▅▁▁▄▄▁▁ beats 200/246medium · avg 47%▇ 0.4%blunt · at its level
knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #41 of 263 · 42% of its score · 14 tests

Beats vera-large here, though they rank higher overall. Trails Solar Decide, Clef-omni, GPT-6 Luna Decisions here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted69.1% ✎▄▄▃▃▂▄▅▇██▅▁ beats 200/246medium · avg 46%▇▇▇▇▇ 11%sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted84.8% ✎▄▆▄▄█▇▇▄▃▁▁▁ beats 214/246easy · avg 66%▇▇ 5.7%typical
Decision Index 0.4.1: MMLU (accuracy) submitted87.2% ✎▁▄▄▃▃▂▅▇▅█▇▁ beats 210/246easy · avg 70%▇▇ 5.5%sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted45.4% ✎▂▆▅▅▆█▆▃▁··▁ beats 154/246medium · avg 39%▇▇ 4.4%blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted86.5% ✎▁··▄█▆▆▆▅▅▃▁ beats 236/246medium · avg 45%▇ 3.7%sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted92.3% ✎█▅█▅▄█▆▄▃▃▁▁ beats 213/246easy · avg 78%▇ 2.6%typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted39.0% ✎▁▁▁▁▁▁▁▂▅█▃▁ beats 221/246hard · avg 22%▇ 2.4%at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted97.7% ✎▂▂▂▂▂▂▁▃▄▆█▆ beats 231/246very easy · avg 90%▇ 1.5%sharp · maxed out
6 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MuSR (accuracy) submitted70.2% ✎▁▁▂█▅▄▁▁▁▁▁▁ beats 217/246medium · avg 60%▇ 1.5%blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted87.7% ✎██▄▃▃▄▁▁···▁ beats 231/246medium · avg 58%▇ 1.2%noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted29.9% ✎▄▇▄▄▄▆▄█▄▃▁▁ beats 239/246hard · avg 16%▇ 1.1%blunt
Decision Index 0.4.1: CLadder (accuracy) submitted88.0% ✎▁███▆▅▃▃▁▁▁▁ beats 213/246easy · avg 71%▇ 1.0%typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted98.8% ✎▁▁▂▁▂▂▂▂▃▆█▅ beats 168/246very easy · avg 96%▇ 0.6%sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted9.2% ✎▁▁▃▃▆█▇▅▅▃▁▁ beats 12/246very hard · avg 13%▇ 0.0%blunt
other tests2 not in a task · 11% of its score
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: private same skills (equated points)62.4900 points ✎▂▂▂▃▃▃▄▅▅▇█▃ beats 227/247avg 41.206 points▇▇▇ 7.3%blunt
Decision Index 0.4.1: private new domains (equated points)67.7000 points ✎▃█▃▃▂▆▃▃▄▄▄▄ beats 208/247avg 38.861 points▇▇ 4.0%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

sourceresultsshare of the scorelicence
Decision Index 0.4.1 · submitted; independent execution unverified42CC BY 4.0
prior · pull toward the middle
weighted average= 69.2

not counted (2)

Decision Index 0.4.1Decision 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 0.4.1Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]68.3%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

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 · sources and licences · json