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AJev lora1 (Gemma 4 26B-A4B)

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AJev lora1 (Gemma 4 26B-A4B) is an open-weights decision model from andyzhang232. Its published size is 25.81B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine ajev-gemma26-lora1; reported model AJev lora1 (Gemma 4 26B-A4B). 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.

60.4±1.3#108 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of AJev lora1 (Gemma 4 26B-A4B), out of 357 with a score, then more from andyzhang232.

#	model	score	where	released
107	OneJev1.5-9B OmniJev	61±4	model files	2026-10-13
108	imajev-4b (DecisionBench c9e5f132) mohit67890	61±2	model files
109	AJev lora1 (Gemma 4 26B-A4B) andyzhang232	60±1	model files
110	decider-35b-a3b (DecisionBench d9783c58) Mapika	60±2	model files	2026-09-20
111	Cerno 9B v1.1 apertixai	60±1	model files	2026-10-19
	more from andyzhang232
27	AJev lm6q (Gemma 4 31B) andyzhang232	69±2	model files
130	AJev lora7 (Gemma 4 12B) andyzhang232	58±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #113 of 250 · 6.7% of its score · 6 tests

Beats Senova-4B v2, Tern-35B-A3B, GEV-26B-Decide here, though they rank higher overall. Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, razorback16 diffgemma (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	81.7% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 126/236	easy · avg 70%	▇ 2.1%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	95.3% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 134/246	very easy · avg 92%	▇ 1.4%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	47.7% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 128/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	63.2% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 106/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: When2Call (accuracy) submitted	85.0% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 173/246	easy · avg 72%	▇ 1.0%	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▁▁▁·▁▁▁▁▃▃█▅ #99 of 258 · 7.1% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Decider 31B (NVFP4), Quyet-1.0-Large here, though they rank higher overall. Trails Jev-Style 2B v4, Sieve 2B v3, StartLux-Decision v1.1 0.8B 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	47.0% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 179/246	medium · avg 38%	▇ 2.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	54.9% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 149/246	medium · avg 47%	▇ 2.5%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	85.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 185/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	78.1% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 163/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	88.3% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 103/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	80.0% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 97/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	53.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #102 of 256 · 22% of its score · 9 tests

Beats jev-brain · Gemma-4-31B (decision readout), AnyJev L0 · Gemma-4-31B (decision readout), decisio 0.6.0 (Gemma 4 31B) (decision readout) here, though they rank higher overall. Trails Decider 4B, jiwo 4B v2, Sieve 4B 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	70.6% ✎	▁▂▃▅▅█▂····▁ beats 165/246	medium · avg 60%	▇▇ 5.4%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	77.1% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 115/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	92.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 153/246	very easy · avg 85%	▇▇ 4.0%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	65.1% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 206/246	medium · avg 44%	▇ 2.6%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	28.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 159/246	hard · avg 22%	▇ 1.5%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	79.1% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 210/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	79.8% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 161/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	79.5% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 168/246	easy · avg 66%	▇ 0.8%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	82.6% ✎	▁···▁▁▁▁▃▆█▃ beats 84/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #121 of 247 · 10% of its score · 6 tests

Beats Bobcat 1.3 (31B), JEV-35B here, though they rank higher overall. Trails vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B), Crivo-400M, Amber 0.4B 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	74.4% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 186/246	medium · avg 61%	▇▇ 4.1%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	64.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 201/246	medium · avg 60%	▇ 2.1%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	62.3% ✎	▁········▁▇█ beats 133/246	medium · avg 60%	▇ 1.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	62.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 182/237	hard · avg 21%	▇ 1.1%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	88.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 125/246	easy · avg 83%	▇ 1.0%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.7% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 103/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #91 of 263 · 44% of its score · 14 tests

Beats StartLux-Decision v1.1 4B, KnowLine 4B Gen5.5, Jeffan-4B-2010 here, though they rank higher overall. Trails Solar Decide, Clef-flash, 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: MMLU-Pro (accuracy) submitted	63.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 171/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	82.8% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 165/246	easy · avg 70%	▇▇▇ 6.5%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	75.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 157/246	easy · avg 66%	▇▇ 6.2%	typical
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	69.4% ✎	▁··▄█▆▆▆▅▅▃▁ beats 184/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	45.4% ✎	▂▆▅▅▆█▆▃▁··▁ beats 155/246	medium · avg 39%	▇ 3.6%	blunt · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	82.8% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 138/246	easy · avg 78%	▇ 3.0%	typical
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.3% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 170/246	very easy · avg 90%	▇ 2.8%	sharp · maxed out
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	35.6% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 210/246	hard · avg 22%	▇ 1.7%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	66.0% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 185/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	98.7% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 163/246	very easy · avg 96%	▇ 1.3%	sharp · maxed out · noisy
Decision Index 0.4.1: CRUXEval (accuracy) submitted	65.8% ✎	██▄▃▃▄▁▁···▁ beats 158/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	71.8% ✎	▁███▆▅▃▃▁▁▁▁ beats 134/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	17.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 149/246	hard · avg 16%	▇ 0.8%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 87/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 9.3% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	54.5000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 166/247	avg 41.206 points	▇▇ 6.0%	blunt
Decision Index 0.4.1: private new domains (equated points)	56.4700 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 174/247	avg 38.861 points	▇ 3.3%	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/andyzhang232 ↗

$ 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		= 60.4

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]	53.2%	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