vera-core-2

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vera-core-2 is an open-weights decision model from scar-ai. Its published size is 1.88B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine vera-core-2; reported model vera-core-2. Type: full fine-tune; 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.

45.8±1.1#237 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of vera-core-2, out of 357 with a score, then more from scar-ai.

#	model	score	where	released
237	Kas 4B kpiya	46±1	model files
238	OpenThai-SystemOne (JevBench mini) iApp Technology	46±2	source code
239	vera-core-2 scar-ai	46±1	model files
240	Kev-4B (JevBench mini) Jared Palmer	46±2	source code
241	TokenRhythm NeoHorse-Jev-4B TokenRhythm	46±1	model files	2026-09-25
	more from scar-ai
20	vera-large scar-ai	70±2	model files
303	vera-spark scar-ai	31±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #160 of 250 · 8.5% of its score · 6 tests

Beats Trio-Spark DI (9B), LiquidAI d1-3B, vLLM-SR Decision 2.0 Nox 4B here, though they rank higher overall. Trails JevK5 Lite, Gevva E2B, 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	92.1% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 90/246	very easy · avg 92%	▇ 3.2%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	61.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 75/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	80.7% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 146/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	64.1% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 119/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	19.3% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 86/243	medium · avg 37%	▇ 0.8%	sharp · at its level · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	75.5% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #182 of 258 · 5.6% of its score · 7 tests

Beats JevK5 9B v0.3.3, Decider 4B, JevK5 v0.3 here, though they rank higher overall. Trails Mola-68M, Bosun v3.1 1.7B LoRA, Dinah-1 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	43.0% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 128/246	medium · avg 38%	▇ 1.9%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	42.8% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 74/246	medium · avg 47%	▇ 1.8%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	80.3% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 148/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	57.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 75/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	86.9% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 90/238	easy · avg 83%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.6% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 158/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	58.1% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #150 of 256 · 24% of its score · 9 tests

Beats Solar Decide, JoshuaSP diffgemma (decision readout), PurpleMIST-Flash-1.0 here, though they rank higher overall. Trails Decider 2B, Crivo-1B 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	84.0% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 106/246	very easy · avg 85%	▇▇▇ 7.6%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	70.5% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 80/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	53.3% ✎	▁▂▃▅▅█▂····▁ beats 78/246	medium · avg 60%	▇▇ 4.8%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	40.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 94/246	medium · avg 44%	▇ 1.8%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	65.9% ✎	▁▁▁▁▁▁▁▂▃▇▇█ beats 62/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	54.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 89/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	87.1% ✎	▁···▁▁▁▁▃▆█▃ beats 115/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	70.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 95/246	easy · avg 66%	▇ 0.8%	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	17.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 96/246	hard · avg 22%	▇ 0.7%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #176 of 247 · 8.4% 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	50.9% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 59/246	medium · avg 61%	▇ 3.7%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	62.6% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 164/246	medium · avg 60%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	72.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 70/246	easy · avg 83%	▇ 1.5%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	60.1% ✎	▁········▁▇█ beats 101/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	3.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 62/237	hard · avg 21%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.5% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 100/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #181 of 263 · 46% 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), Cam1, Intelif Qwen3-4B 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	40.7% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 81/246	medium · avg 46%	▇▇▇ 8.4%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	64.0% ✎	▁▄▄▃▃▃▅▇▅█▇▁ beats 79/246	easy · avg 70%	▇▇▇ 7.4%	sharp · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	87.0% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 79/246	very easy · avg 90%	▇▇▇ 6.7%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	51.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 65/246	easy · avg 66%	▇▇ 6.2%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	95.2% ✎	▁▁▂▁▂▂▂▃▃▆█▅ beats 83/246	very easy · avg 96%	▇▇ 4.3%	sharp · maxed out · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	68.9% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 73/246	easy · avg 78%	▇ 3.4%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	44.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 126/246	medium · avg 45%	▇ 2.8%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	36.7% ✎	▂▆▅▅▆█▆▃▁··▁ beats 91/246	medium · avg 39%	▇ 2.5%	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	60.1% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 133/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	37.7% ✎	██▄▃▃▄▁▁···▁ beats 38/246	medium · avg 58%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	58.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 60/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	27.2% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 118/246	hard · avg 22%	▇ 0.9%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	10.3% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 62/246	hard · avg 16%	▇ 0.5%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 129/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.9% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	38.9500 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 94/247	avg 41.206 points	▇▇ 4.4%	blunt
Decision Index 0.4.1: private new domains (equated points)	18.0700 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 68/247	avg 38.861 points	▇ 2.4%	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/scar-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

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		= 45.8

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	75.5%	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]	58.1%	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

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