whatmodel.sh / decision / Xor 26B-A4B v1.2

Xor 26B-A4B v1.2 is an open-weights decision model from Juspay Technologies, released 16 October 2026. Its published size is 25.81B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine xor-26b-a4b-v1.2; reported model Xor 26B-A4B v1.2. 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.

63.3±1.4#72 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Xor 26B-A4B v1.2, out of 357 with a score, then more from Juspay Technologies.

#modelscorewhereRAMreleased
70KnowLine 35B-A3B Gen1 PelaAI64±4model files2026-10-12
71jev-vision-27b e12ex264±4model files
72Xor 26B-A4B v1.2 Juspay Technologies63±1model files2026-10-16
73Senova-4B v2 WangSenQWQ63±1model files
74Clef Cloudflare63±1api $0.24/M input tokens +local~68GB2026-10
more from Juspay Technologies
123Xor 1.2 Juspay Technologies59±1model files2026-09-28
148xor-26b-a4b-v1.1 Juspay Technologies56±4model files2026-10-09

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #106 of 250 · 6.3% of its score · 6 tests

Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, mmastrac diffgemma (decision readout) here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: API-Bank (accuracy) submitted86.0% ✎▁▁▁▁▁▁▁▂▃▂█▂ beats 193/236easy · avg 70%▇ 1.9%sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted95.7% ✎▁▂▁▁▁▂▂▄▅▆█▁ beats 141/246very easy · avg 92%▇ 1.2%sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted60.2% ✎█▁▁▃▄▄▆▄▁▂▁▃ beats 147/243medium · avg 37%▇ 1.2%sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted66.1% ✎▁▁▁▁▁·▁▁▁▄█▁ beats 161/246medium · avg 60%▇ 1.1%blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted64.6% ✎▁▁▁▂▃▅▅▆█▇█▃ beats 78/246easy · avg 72%▇ 1.0%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▁▁▁·▁▁▁▁▃▃█▅ #51 of 258 · 7.4% of its score · 7 tests

Beats H2O Lightning 31B v1.1, AutoTrust-JEV-27B v1.1, d1.1 (hosted) here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 8B SH (v4), StartLux-Decision v1.1 2B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted48.9% ✎▁▁▁▁▁▁▁▂▂▄▇█ beats 216/246medium · avg 38%▇ 2.9%blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted58.8% ✎▁▁▁▁▁▁▂▂▃▃█▅ beats 203/246medium · avg 47%▇ 2.6%at its level
Decision Index 0.4.1: HoVer (accuracy) submitted78.3% ✎▆▆▇▅▄▄▃▇▄█▆▄ beats 135/246easy · avg 74%▇ 0.6%blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted80.8% ✎█▅▅▄▃▂▁▁▁▁·▁ beats 174/245easy · avg 70%▇ 0.6%noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted93.3% ✎▁▁▁▁▁▁▁▂▃▆█▄ beats 180/238easy · avg 83%▇ 0.3%sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted82.6% ✎▁·▁▁▁▁▁▁▂█▇█ beats 113/238easy · avg 79%▇ 0.3%noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted25.1% ✎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▂▂▂▃▂▅▆▃█▆▄▃ #62 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.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ANLI (macro-F1) submitted75.8% ✎▁▂▃▅▅█▂····▁ beats 203/246medium · avg 60%▇▇ 5.5%at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted82.0% ✎▁▁▁▂▂▃▃▄▇▇█▄ beats 172/246easy · avg 74%▇▇ 5.3%typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted94.8% ✎▂▄▂▂▄▇▃▇█▅▃▁ beats 191/246very easy · avg 85%▇ 3.5%sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted63.4% ✎▁·▁·▁▁▂▄▅█▇▄ beats 201/246medium · avg 44%▇ 2.7%at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted27.8% ✎▁··▂▃▃▅▇█▇▃▃ beats 157/246hard · avg 22%▇ 1.6%at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted67.0% ✎▁▁▁▂▅▄▄▂▄▆█▄ beats 122/246medium · avg 62%▇ 1.1%at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted76.7% ✎▁▁▁▁▁▁▁▂▂▇▇█ beats 133/246easy · avg 71%▇ 1.0%noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted80.0% ✎▁▁▁▁▁▁▁▁▁▃▆█ beats 175/246easy · avg 66%▇ 0.8%noisy
1 more test
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: FinEntity (macro-F1) submitted91.3% ✎▁···▁▁▁▁▃▆█▃ beats 168/246easy · avg 84%▇ 0.5%noisy
arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #26 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 Clef-omni, Clef, Senova-4B v2 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: New Yorker (accuracy) submitted72.7% ✎▁▁▂▃▃▃▇▅█▅▃▁ beats 169/246medium · avg 61%▇▇ 4.1%at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted66.3% ✎▁·▁▃▂▂▅█▄▂▁▁ beats 218/246medium · avg 60%▇ 2.2%blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted61.7% ✎▄▅▅▃▆▅▃▅▂▅▃█ beats 179/237hard · avg 21%▇ 1.3%sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted67.3% ✎▁········▁▇█ beats 227/246medium · avg 60%▇ 1.2%blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted96.8% ✎▁█▄▄▅█▆▅▄▁▁▁ beats 220/246easy · avg 83%▇ 0.9%sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted46.8% ✎▁▂▄█▇▅▁▁▄▄▁▁ beats 158/246medium · avg 47%▇ 0.4%blunt · at its level
knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #67 of 263 · 44% of its score · 14 tests

Beats StartLux-Decision v1.1 9B, Sieve 27B v2, RSI-Jev v6.1 VL 27B (effort auto) here, though they rank higher overall. Trails Solar Decide, Clef-flash, Clef-omni here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted66.8% ✎▄▄▃▃▂▄▅▇██▅▁ beats 189/246medium · avg 46%▇▇▇▇▇ 11%sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted85.2% ✎▁▄▄▃▃▂▅▇▅█▇▁ beats 190/246easy · avg 70%▇▇ 6.2%sharp
Decision Index 0.4.1: BBH (accuracy) submitted78.0% ✎▄▆▄▄█▇▇▄▃▁▁▁ beats 179/246easy · avg 66%▇▇ 6.1%typical
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted45.9% ✎▂▆▅▅▆█▆▃▁··▁ beats 160/246medium · avg 39%▇▇ 3.8%blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted75.2% ✎▁··▄█▆▆▆▅▅▃▁ beats 205/246medium · avg 45%▇ 3.7%sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted86.5% ✎█▅█▅▄█▆▄▃▃▁▁ beats 172/246easy · avg 78%▇ 2.8%typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted97.1% ✎▂▂▂▂▂▂▁▃▄▆█▆ beats 201/246very easy · avg 90%▇ 2.3%sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted37.6% ✎▁▁▁▁▁▁▁▂▅█▂▁ beats 215/246hard · avg 22%▇ 1.9%at its level
6 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MuSR (accuracy) submitted65.4% ✎▁▁▂█▅▄▁▁▁▁▁▁ beats 181/246medium · avg 60%▇ 1.4%blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted70.9% ✎██▄▃▃▄▁▁···▁ beats 170/246medium · avg 58%▇ 1.2%at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted73.3% ✎▁███▆▅▃▃▁▁▁▁ beats 146/246easy · avg 71%▇ 1.0%typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted99.0% ✎▁▁▂▁▂▂▂▂▃▆█▅ beats 180/246very easy · avg 96%▇ 1.0%sharp · maxed out · noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted22.2% ✎▄▇▄▄▄▆▄█▄▁▁▁ beats 193/246hard · avg 16%▇ 0.9%blunt
Decision Index 0.4.1: HLE (accuracy) submitted10.4% ✎▁▁▂▃▆█▇▅▅▃▁▁ beats 40/246very hard · avg 13%▇ 0.0%blunt
other tests2 not in a task · 10% of its score
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: private same skills (equated points)58.3700 points ✎▂▂▂▃▃▃▄▅▅▇█▃ beats 198/247avg 41.206 points▇▇▇ 6.4%blunt
Decision Index 0.4.1: private new domains (equated points)61.0600 points ✎▃█▃▃▂▆▃▃▄▄▄▄ beats 189/247avg 38.861 points▇ 3.5%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/juspay ↗

$ 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= 63.3

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]25.1%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