Gevva E2B

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Gevva E2B is an open-weights decision model from davidburhans. Its published size is 5.1B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine gevva-e2b; reported model Gevva E2B. 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.

37.1±1.1#275 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Gevva E2B, out of 357 with a score, then more from davidburhans.

#	model	score	where	released
275	kev-0.6b (DecisionBench dece6dba) Jared Palmer	37±2	model files
276	jiwo 0.8B v2 eljiwo	37±1	model files	2026-10-10
277	Gevva E2B davidburhans	37±1	model files
278	mojev (DecisionBench 0c8695b6) MoLeMo-Lab	37±2	request access
279	Crivo-400M tardellirs	37±1	model files
	more from davidburhans
259	Gevva E4B davidburhans	42±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #150 of 250 · 9.3% 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 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	92.6% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 102/246	very easy · avg 92%	▇▇ 4.8%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	48.2% ✎	▁▁▁▁▁▁▁▃▃▂█▂ beats 46/236	easy · avg 70%	▇ 2.3%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	75.2% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 113/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	58.5% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 58/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 45/243	medium · avg 37%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.7% ✎	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▁▁▁·▁▁▁▃▃▃█▅ #218 of 258 · 4.9% of its score · 7 tests

Beats Intelif Qwen3-4B, mini-jev Qwen3-4B (decision readout), open-jev (pngwn) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Crivo-32M v2, Mola-68M here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	32.3% ✎	▁▁▁▁▁▁▂▃▃▃█▅ beats 40/246	medium · avg 47%	▇ 1.5%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	34.8% ✎	▁▁▁▁▁▁▁▂▃▄▇█ beats 71/246	medium · avg 38%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	68.4% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 41/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	58.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 39/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	67.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 117/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	63.3% ✎	▁·▁▁▁▁▁▁▃█▇█ beats 29/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	64.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #217 of 256 · 24% of its score · 9 tests

Beats Saina Helm 2 Omni (0.8B) here, though they rank higher overall. Trails LiquidAI d1-omni-600M, DecisionTune 1.0, vera-spark 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	56.8% ✎	▂▄▃▂▄▇▃▇█▅▃▁ beats 39/246	very easy · avg 85%	▇▇▇▇ 9.3%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	68.9% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 74/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	44.7% ✎	▁▂▃▅▅█▂····▁ beats 47/246	medium · avg 60%	▇▇ 4.2%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	30.9% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 63/246	medium · avg 44%	▇ 1.4%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	55.1% ✎	▁▁▁▁▁▁▁▃▂▇▇█ beats 40/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	74.7% ✎	▁···▁▁▁▁▃▆█▃ beats 54/246	easy · avg 84%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	37.4% ✎	▁▁▁▃▅▄▄▂▄▆█▄ beats 21/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	15.6% ✎	▁▁▁▁▁▁▃▁▁▃▆█ beats 19/246	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	11.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 66/246	hard · avg 22%	▇ 0.5%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #191 of 247 · 7.6% of its score · 6 tests

Beats Kev 9B v2, vLLM-SR d3-nano (2B), Valen-4B here, though they rank higher overall. Trails Qwen-2.5-1B-RLCD (decision readout), Bekko System One v0 68M, Crivo-17M 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	36.0% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 29/246	medium · avg 61%	▇ 3.2%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	62.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 56/246	easy · avg 83%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	58.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 80/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	60.2% ✎	▁········▁▇█ beats 102/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	33.7% ✎	▁▃▄█▇▅▁▁▄▄▁▁ beats 13/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	14.2% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 116/237	hard · avg 21%	▇ 0.2%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▂▂▃▃▃▅▅▆█▂ #202 of 263 · 48% of its score · 14 tests

Beats GLiClass v4 edge (0.4B), Crivo-1B, vLLM-SR vela3-fast (Vela 3.0, 0.4B) here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), DM-JEPA 1.1, Sieve 2B 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	73.7% ✎	▂▂▂▂▂▃▁▃▄▆█▆ beats 60/246	very easy · avg 90%	▇▇▇▇ 9.5%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	86.5% ✎	▁▁▂▁▂▃▂▂▃▆█▅ beats 58/246	very easy · avg 96%	▇▇▇ 8.2%	sharp · noisy
Decision Index 0.4.1: MMLU (accuracy) submitted	54.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 64/246	easy · avg 70%	▇▇▇ 7.0%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	28.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 59/246	medium · avg 46%	▇▇ 6.1%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	52.9% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 70/246	easy · avg 66%	▇▇ 5.7%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	56.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 34/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	26.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 34/246	medium · avg 39%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	21.8% ✎	▁··▄█▆▆▆▅▅▃▁ beats 46/246	medium · avg 45%	▇ 2.0%	sharp · 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	50.9% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 37/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	56.4% ✎	▁███▆▅▃▃▁▁▁▁ beats 49/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	36.0% ✎	██▄▃▃▄▁▁···▁ beats 32/246	medium · avg 58%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	21.9% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 83/246	hard · avg 22%	▇ 0.6%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	11.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 80/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	14.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 175/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.0% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	27.0500 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 57/247	avg 41.206 points	▇▇ 3.9%	blunt
Decision Index 0.4.1: private new domains (equated points)	20.0700 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 74/247	avg 38.861 points	▇ 2.1%	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 0.4.1 100%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 100%	CC BY 4.0
prior · pull toward the middle		▇ 0%
weighted average		= 37.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.7%	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]	64.2%	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

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