whatmodel.sh / decision / Sieve 27B v2

Sieve 27B v2 is an open-weights decision model from Sthānika AI, released 18 October 2026. Its published size is 27.78B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine sieve-27b-v2; reported model Sieve 27B v2. 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

66.9±1.4#37 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Sieve 27B v2, out of 357 with a score, then more from Sthānika AI.

#modelscorewhereRAMreleased
35mogan-decision-31B-it Mogan AI67±1model files
36oenogarum (Gemma 4 31B) plantwaterer67±1model files
37Sieve 27B v2 Sthānika AI67±1model files2026-10-18
38H2O Lightning 31B H2O.ai67±4request access
39Aleria Judge 1.1.1 (Gemma 4 31B) (decision readout) ALERIA-ML67±1source code2026-10-19
more from Sthānika AI
3Sieve 31B v3 Sthānika AI74±2model files2026-10-27
79Sieve-Vision-27B Sthānika AI63±4model files
137Sieve 9B v2 Sthānika AI57±1model files2026-10-13

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #93 of 250 · 5.8% of its score · 6 tests

Trails OneJev1.6-0.8B, Jev-Omni, baselabs joey-1 (2B) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: API-Bank (accuracy) submitted89.0% ✎▁▁▁▁▁▁▁▂▃▂█▃ beats 227/236easy · avg 70%▇ 1.7%sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted68.5% ✎▁▁▁▁▁·▁▁▁▄█▁ beats 214/246medium · avg 60%▇ 1.1%blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted100.0% ✎█▁▁▃▄▄▆▄▁▂▁▃ beats 236/243medium · avg 37%▇ 1.0%sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted84.8% ✎▁▁▁▂▃▅▅▆█▇█▃ beats 170/246easy · avg 72%▇ 1.0%noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted96.0% ✎▁▂▁▁▁▂▂▄▅▆█▁ beats 152/246very easy · avg 92%▇ 0.9%sharp · maxed out · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted79.8% ✎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▁▁▁·▁▁▁▁▃▃█▅ #24 of 258 · 7.8% of its score · 7 tests

Beats KnowLine 31B Gen1, Ainvest-Decision-27B v1.0, Perplexity Decider v1.1 (27B) 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) submitted46.1% ✎▁▁▁▁▁▁▁▂▂▄▇█ beats 168/246medium · avg 38%▇ 3.2%blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted61.3% ✎▁▁▁▁▁▁▂▂▃▃█▅ beats 223/246medium · avg 47%▇ 2.8%at its level
Decision Index 0.4.1: HoVer (accuracy) submitted88.0% ✎▆▆▇▅▄▄▃▇▄█▆▄ beats 216/246easy · avg 74%▇ 0.6%blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted96.7% ✎█▅▅▄▃▂▁▃▁▁·▁ beats 237/245easy · avg 70%▇ 0.6%noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted90.0% ✎▁·▁▁▁▁▁▁▂█▇█ beats 178/238easy · avg 79%▇ 0.3%noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted90.9% ✎▁▁▁▁▁▁▁▂▃▆█▄ beats 140/238easy · avg 83%▇ 0.3%sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted46.5% ✎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▂▂▂▃▂▅▆▃█▆▄▃ #25 of 256 · 22% of its score · 9 tests

Beats KnowLine 31B Gen1, Ainvest-Decision-27B v1.0, WeMM-JEV-27B here, though they rank higher overall. Trails Clef-flash, Clef-omni, JEV-35B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ANLI (macro-F1) submitted75.2% ✎▁▂▃▅▅█▂····▁ beats 197/246medium · avg 60%▇▇ 5.5%typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted85.4% ✎▁▁▁▂▂▃▃▄▇▇█▄ beats 219/246easy · avg 74%▇▇ 5.2%typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted97.0% ✎▂▄▂▂▄▇▃▇█▅▃▁ beats 224/246very easy · avg 85%▇ 2.9%sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted47.3% ✎▁·▁·▁▁▂▄▅█▇▄ beats 120/246medium · avg 44%▇ 2.8%at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted48.3% ✎▁··▂▃▃▅▇█▇▃▃ beats 220/246hard · avg 22%▇ 1.9%at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted78.1% ✎▁▁▁▂▅▄▄▂▄▆█▄ beats 197/246medium · avg 62%▇ 1.1%typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted83.4% ✎▁▁▁▁▁▁▁▂▂▇▇█ beats 201/246easy · avg 71%▇ 1.0%noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted74.0% ✎▁▁▁▁▁▁▁▁▁▃▆█ beats 122/246easy · avg 66%▇ 0.7%noisy
1 more test
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: FinEntity (macro-F1) submitted93.2% ✎▁···▁▁▁▁▃▆█▃ beats 197/246easy · avg 84%▇ 0.5%maxed out · noisy
arts & human taste▁▇▄▃▅▅█▅▄▃▁▁ #14 of 247 · 10% of its score · 6 tests

Beats Jeffan-31b-1710, KnowLine 31B Gen1, vLLM-SR d3-turbo v1.1 (27B) here, though they rank higher overall. Trails AnyJev L0 · Gemma-4-31B (decision readout) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: New Yorker (accuracy) submitted78.0% ✎▁▁▂▃▃▃▇▅█▅▃▁ beats 207/246medium · avg 61%▇▇ 4.0%typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted60.1% ✎▁·▁▃▂▂▅█▄▂▁▁ beats 97/246medium · avg 60%▇ 2.4%blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted83.3% ✎▄▅▅▃▆▅▃▅▂▅▃█ beats 233/237hard · avg 21%▇ 1.3%sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted64.8% ✎▁········▁▇█ beats 174/246medium · avg 60%▇ 1.3%blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted98.0% ✎▁█▄▄▅█▆▅▄▃▁▁ beats 233/246easy · avg 83%▇ 0.9%sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted65.7% ✎▁▂▄█▇▅▁▁▄▄▃▁ beats 241/246medium · avg 47%▇ 0.4%blunt · at its level
knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #79 of 263 · 43% of its score · 14 tests

Beats StartLux-Decision v1.1 9B here, though they rank higher overall. Trails Solar Decide, Clef-flash, Decider chat · Qwen3.6-27B (decision readout) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted62.4% ✎▄▄▃▃▂▄▅▇██▅▁ beats 167/246medium · avg 46%▇▇▇▇▇ 11%sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted88.2% ✎▄▆▄▄█▇▇▄▃▁▁▁ beats 227/246easy · avg 66%▇▇ 5.9%typical
Decision Index 0.4.1: MMLU (accuracy) submitted82.3% ✎▁▄▄▃▃▂▅▇▅█▇▁ beats 163/246easy · avg 70%▇▇ 5.8%sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted49.5% ✎▂▆▅▅▆█▆▃▁··▁ beats 192/246medium · avg 39%▇▇ 4.2%blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted72.0% ✎▁··▄█▆▆▆▅▅▃▁ beats 194/246medium · avg 45%▇ 3.7%sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted95.2% ✎█▅█▅▄█▆▄▃▃▁▁ beats 234/246easy · avg 78%▇ 2.7%typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted42.9% ✎▁▁▁▁▁▁▁▂▅█▃▁ beats 233/246hard · avg 22%▇ 2.2%at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted96.2% ✎▂▂▂▂▂▂▁▃▄▆█▆ beats 167/246very easy · avg 90%▇ 1.8%sharp · maxed out
6 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MuSR (accuracy) submitted88.3% ✎▁▁▂█▅▄▁▁▁▁▃▁ beats 242/246medium · avg 60%▇ 1.4%blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted81.8% ✎██▄▃▃▄▁▁···▁ beats 202/246medium · avg 58%▇ 1.2%at its level · noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted24.7% ✎▄▇▄▄▄▆▄█▄▁▁▁ beats 219/246hard · avg 16%▇ 1.0%blunt
Decision Index 0.4.1: CLadder (accuracy) submitted93.3% ✎▁███▆▅▃▃▃▁▁▁ beats 232/246easy · avg 71%▇ 1.0%typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted98.5% ✎▁▁▂▁▂▂▂▂▃▆█▅ beats 157/246very easy · avg 96%▇ 0.7%sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted10.4% ✎▁▁▂▃▆█▇▅▅▃▁▁ beats 41/246very 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)59.6700 points ✎▂▂▂▃▃▃▄▅▅▇█▃ beats 207/247avg 41.206 points▇▇▇ 6.9%blunt
Decision Index 0.4.1: private new domains (equated points)60.2300 points ✎▃█▃▃▂▆▃▃▄▄▄▄ beats 186/247avg 38.861 points▇▇ 3.8%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/sthanika-ai ↗

$ 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= 66.9

not counted (2)

Decision Index 0.4.1Decision 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 0.4.1Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]46.5%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