Gevva E4B

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Gevva E4B is an open-weights decision model from davidburhans. Its published size is 8B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine gevva-e4b; reported model Gevva E4B. Type: full fine-tune; technique: encoder. 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.

41.6±1.1#257 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Gevva E4B, out of 357 with a score, then more from davidburhans.

#	model	score	where
257	vLLM-SR vela3-fast (Vela 3.0, 0.4B) vLLM Semantic Router	42±1	model files
258	Cam1 cbuk10001	42±1	model files
259	Gevva E4B davidburhans	42±1	model files
260	Qwen3-Reranker-4B (DecisionBench 22e68366) Alibaba (Qwen)	41±2	model files
261	mini-jev Qwen3-4B (decision readout) r-ms	41±1	source code
	more from davidburhans
277	Gevva E2B davidburhans	37±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #147 of 250 · 8.9% of its score · 6 tests

Beats Cerno 4B v1.1, Trio-Spark DI (9B), Decider 35B-A3B here, though they rank higher overall. Trails JevK5 Lite, 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: BFCL (case exact accuracy) submitted	92.7% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 104/246	very easy · avg 92%	▇▇ 3.9%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	55.1% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 60/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	71.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 102/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	60.8% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 72/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	17.1% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 81/243	medium · avg 37%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.8% ✎	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▁▁▁·▁▁▁▃▃▃█▅ #204 of 258 · 5.3% of its score · 7 tests

Beats SemIf Qwen3.5-4B Base (decision readout), Metask-Jev-4B, Jobe Qwen3.5-4B (decision readout) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Mola-68M, Bosun v3.1 1.7B LoRA 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	38.6% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 90/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	37.9% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 54/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	57.8% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 38/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	71.7% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 44/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	62.7% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 99/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	65.6% ✎	▁·▁▁▁▁▁▁▃█▇█ beats 32/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	65.2% ✎	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▂▂▂▃▃▅▆▃█▆▄▃ #198 of 256 · 24% of its score · 9 tests

Beats TokenRhythm NeoHorse-Jev-4B, vLLM-SR vela3-fast (Vela 3.0, 0.4B) here, though they rank higher overall. Trails DecisionTune 1.0, vera-spark, JEV FLAN-T5 Large public v2 (342M) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: HellaSwag (accuracy) submitted	73.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 58/246	very easy · avg 85%	▇▇▇ 8.5%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	68.5% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 71/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	31.0% ✎	▁▃▃▅▅█▂····▁ beats 18/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	36.9% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 79/246	medium · avg 44%	▇ 1.6%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	56.7% ✎	▁▁▁▁▁▁▁▃▂▇▇█ beats 46/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	39.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 30/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	77.9% ✎	▁···▁▁▁▁▃▆█▃ beats 62/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	36.7% ✎	▁▁▁▁▁▁▁▃▁▃▆█ beats 36/246	easy · avg 66%	▇ 0.7%	at its level · noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ACOS (per-review F1) submitted	12.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 67/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #178 of 247 · 8.0% of its score · 6 tests

Beats Sieve 9B, Kev 9B v2, vLLM-SR d3-nano (2B) here, though they rank higher overall. Trails Bekko System One v0 68M, Crivo-17M, Crivo-32M v2 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	44.7% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 47/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	72.1% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 69/246	easy · avg 83%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	59.8% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 92/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	59.7% ✎	▁········▁▇█ beats 99/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	13.1% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 112/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.1% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 53/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #182 of 263 · 47% of its score · 14 tests

Beats baselabs joey-1 (2B), Aurelis-2B, StartLux-Decision v1.1 0.8B here, though they rank higher overall. Trails mini-jev Qwen3-4B (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	87.0% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 80/246	very easy · avg 90%	▇▇▇ 8.2%	sharp
Decision Index 0.4.1: MMLU (accuracy) submitted	63.6% ✎	▁▄▄▃▃▃▅▇▅█▇▁ beats 78/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	36.4% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 74/246	medium · avg 46%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	59.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 81/246	easy · avg 66%	▇▇ 6.0%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	94.1% ✎	▁▁▂▁▂▂▂▃▃▆█▅ beats 78/246	very easy · avg 96%	▇▇ 6.0%	sharp · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	60.4% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 47/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	27.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 67/246	medium · avg 45%	▇ 2.4%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	32.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 69/246	medium · avg 39%	▇ 2.2%	blunt · 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	58.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 118/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	39.6% ✎	██▄▃▃▄▁▁···▁ beats 52/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	56.2% ✎	▁███▆▅▃▃▁▁▁▁ beats 48/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	27.8% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 123/246	hard · avg 22%	▇ 0.8%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	12.6% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 89/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	10.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 42/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.4% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	30.3400 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 66/247	avg 41.206 points	▇▇ 4.1%	blunt
Decision Index 0.4.1: private new domains (equated points)	27.5300 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 92/247	avg 38.861 points	▇ 2.3%	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/davidburhans ↗

$ 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		= 41.6

not counted (2)

Decision Index 0.4.1	Decision 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 0.4.1	Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]	65.2%	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

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data updated 2026-11-03 02:37 UTC · sources and licences · json