Von 1.3

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Von 1.3 is an open-weights decision model from wfzyx, released 28 September 2026. Its published size is 0.4B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine von-1.3; reported model Von 1.3. 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

Release date ↗ · Weights licence ↗ · Parameter count ↗

Publisher parameter count; includes the served backbone, not just adapter size.

24.7±1.0#327 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Von 1.3, out of 357 with a score, then more from wfzyx.

#	model	score	where	RAM	released
327	rlcd-modernbert-151m (DecisionBench 8af2496e) heman10x	26±2	model files
328	JevK5 Lite alibiserikbay	25±1	model files
329	Von 1.3 wfzyx	25±1	model files		2026-09-28
330	Bosun v3.1 0.6B LoRA Hanno Labs	25±1	model files		2026-09-22
331	laya (DecisionBench 1c5edc17) ConvAI Innovations	25±1	local	~1.7GB
	more from wfzyx
271	Von 1.3 (JevBench mini) wfzyx	39±2	source code

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #245 of 250 · 10% of its score · 6 tests

Trails LFM2.5-350M-RLCD, Supersonic Labs Julia 1, CLM-v0.1-8B Qwen3-8B heads 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	37.0% ✎	▁▃▁▁▁▂▂▄▅▆█▁ beats 5/246	very easy · avg 92%	▇▇▇ 6.6%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	0.4% ✎	▃▁▁▁▁▁▁▂▃▂█▂ beats 0/236	easy · avg 70%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	47.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 37/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	27.3% ✎	▁▁▁▁▃·▁▁▁▄█▁ beats 13/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 34/243	medium · avg 37%	▇ 0.1%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	54.9% ✎	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▁▁▁·▁▃▁▁▃▃█▅ #238 of 258 · 4.5% of its score · 7 tests

Beats Sieve 2B, DM-JEPA 1.1, Together Tev1 Qwen3.5-0.8B here, though they rank higher overall. Trails MoganAI Lavoir ModernBERT-large, 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: Amazon ESCI (macro-F1) submitted	26.3% ✎	▁▁▁▁▁▁▃▂▃▃█▅ beats 22/246	medium · avg 47%	▇ 1.2%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	17.7% ✎	▁▁▁▁▃▁▁▂▂▄▇█ beats 13/246	medium · avg 38%	▇ 1.2%	blunt
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	59.9% ✎	▁▁▁▁▁▁▁▃▃▆█▄ beats 32/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	60.5% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 51/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 16/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	75.7% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 68/238	easy · avg 79%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	26.8% ✎	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▂▃▂▃▂▅▆▃█▆▄▃ #239 of 256 · 23% of its score · 9 tests

Beats Bosun v3.1 1.7B LoRA, Jev-Style 0.8B v3, Crivo-32M v2 here, though they rank higher overall. Trails CLM-v0.1-8B Qwen3-8B heads, Qwen-2.5-1B-RLCD (decision readout), MoganAI Lavoir ModernBERT-large 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	37.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 17/246	very easy · avg 85%	▇▇▇▇ 9.5%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	56.8% ✎	▁▁▁▂▃▃▃▄▇▇█▄ beats 32/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	46.6% ✎	▁▂▃▅▅█▂····▁ beats 51/246	medium · avg 60%	▇ 3.6%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	61.2% ✎	▁···▁▁▁▃▃▆█▃ beats 25/246	easy · avg 84%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	18.9% ✎	▁·▁·▁▁▃▄▅█▇▄ beats 21/246	medium · avg 44%	▇ 1.0%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	29.0% ✎	▁▁▁▁▃▁▁▂▂▇▇█ beats 15/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	37.4% ✎	▁▁▁▃▅▄▄▂▄▆█▄ beats 22/246	medium · avg 62%	▇ 0.7%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	41.1% ✎	▁▁▁▁▁▁▁▁▃▃▆█ beats 39/246	easy · avg 66%	▇ 0.6%	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	3.5% ✎	▁··▃▃▃▅▇█▇▃▃ beats 14/246	hard · avg 22%	▇ 0.3%	too hard for it · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #210 of 247 · 7.0% of its score · 6 tests

Beats Valen-4B, Saracura PT-BR 4B, TokenRhythm NeoHorse-Jev-4B here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Qwen-2.5-1B-RLCD (decision readout) 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	24.6% ✎	▁▃▂▃▃▃▇▅█▅▃▁ beats 9/246	medium · avg 61%	▇ 2.7%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	53.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 37/246	easy · avg 83%	▇ 1.8%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	47.0% ✎	▁·▃▃▂▂▅█▄▂▁▁ beats 5/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	52.3% ✎	▁········▁▇█ beats 38/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	28.9% ✎	▃▂▄█▇▅▁▁▄▄▁▁ beats 1/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	2.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 57/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▃▂▂▂▃▃▅▅▆█▂ #242 of 263 · 49% of its score · 14 tests

Beats Amber 0.4B, Dinah-1, Crivo-68M here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	57.9% ✎	▁▁▃▁▂▂▂▂▃▆█▅ beats 20/246	very easy · avg 96%	▇▇▇▇▇▇ 14%	sharp · at its level · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	42.1% ✎	▂▂▃▂▂▂▁▃▄▆█▆ beats 20/246	very easy · avg 90%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	34.6% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 19/246	easy · avg 70%	▇▇ 6.0%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	38.2% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 30/246	easy · avg 66%	▇▇ 4.8%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	16.3% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 25/246	medium · avg 46%	▇▇ 3.8%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	54.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 27/246	easy · avg 78%	▇ 3.7%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	24.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 16/246	medium · avg 39%	▇ 1.6%	blunt
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	16.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 1/246	medium · avg 45%	▇ 1.2%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	56.5% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 91/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	68.6% ✎	▁███▆▅▃▃▁▁▁▁ beats 122/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	43.3% ✎	██▄▃▃▄▁▁···▁ beats 77/246	medium · avg 58%	▇ 0.7%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	1.5% ✎	▁▁▃▁▁▁▁▂▅█▂▁ beats 19/246	hard · avg 22%	▇ 0.4%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	7.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 10/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	19.2% ✎	▁▁▂▃▆█▇▅▅▃▁▃ beats 242/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 5.7% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	11.9000 points ✎	▂▃▂▃▃▃▄▅▅▇█▃ beats 17/247	avg 41.206 points	▇ 3.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	11.2800 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 27/247	avg 38.861 points	▇ 2.0%	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/wfzyx ↗

$ 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		= 24.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	54.9%	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]	26.8%	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