whatmodel.sh / decision / vLLM-SR vela3-fast (Vela 3.0, 0.4B)

vLLM-SR vela3-fast (Vela 3.0, 0.4B)

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vLLM-SR vela3-fast (Vela 3.0, 0.4B) is an open-weights decision model from vLLM Semantic Router. Its published size is 0.38B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine vela3-fast; reported model vLLM-SR vela3-fast (Vela 3.0, 0.4B). 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.

42.1±1.1#255 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of vLLM-SR vela3-fast (Vela 3.0, 0.4B), out of 357 with a score, then more from vLLM Semantic Router.

#	model	score	where	released
255	OneJev1.5-0.8B OmniJev	42±4	model files	2026-10-13
256	jevhome-ettin-1b (JevBench mini) Jibril Frej	42±2	source code
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
	more from vLLM Semantic Router
8	vLLM-SR d3-ultra (Decision 3.0, 27B) vLLM Semantic Router	72±1	model files
9	vLLM-SR d3-turbo v1.1 (27B) vLLM Semantic Router	72±1	model files
25	vLLM-SR d3 (27B) vLLM Semantic Router	69±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #163 of 250 · 8.8% of its score · 6 tests

Beats LiquidAI d1-3B, vLLM-SR Decision 2.0 Nox 4B, Decider 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	91.7% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 87/246	very easy · avg 92%	▇▇ 3.9%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	73.0% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 97/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	83.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 165/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	60.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 68/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	71.6% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 173/243	medium · avg 37%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	54.2% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #105 of 258 · 5.3% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Decider 31B (NVFP4), Quyet-1.0-Large here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	26.5% ✎	▁▁▁▁▁▁▃▂▂▄▇█ beats 35/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	54.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 148/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	86.5% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 203/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	94.0% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 193/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	90.8% ✎	█▅▅▄▃▃▁▁▁▁·▁ beats 216/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	92.6% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 224/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	41.3% ✎	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▂▂▂▃▃▅▆▃█▆▄▃ #202 of 256 · 24% of its score · 9 tests

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	71.6% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 53/246	very easy · avg 85%	▇▇▇ 8.4%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	68.7% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 72/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	56.1% ✎	▁▂▃▅▅█▂····▁ beats 87/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	50.7% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 137/246	medium · avg 44%	▇ 1.7%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	77.8% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 139/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	76.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 181/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	87.7% ✎	▁···▁▁▁▁▃▆█▃ beats 119/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	73.7% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 119/246	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	48.8% ✎	▁··▂▃▃▅▇█▇▃▃ beats 221/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #95 of 247 · 8.0% of its score · 6 tests

Beats Jev 1.13, jev-brain · Gemma-4-31B (decision readout), Jeffan-4B-2010 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	58.5% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 90/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	91.0% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 154/246	easy · avg 83%	▇ 1.6%	sharp · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	63.4% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 180/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	52.6% ✎	▁········▁▇█ beats 43/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	66.9% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 192/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	56.0% ✎	▁▂▄█▇▅▁▃▄▄▁▁ beats 187/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▃▂▃▃▅▅▆█▂ #221 of 263 · 47% of its score · 14 tests

Trails laya (DecisionBench 1c5edc17), LFM2.5-2.6B-RLCD, InternLM Intern-Decision Qwen3.5-0.8B 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	58.2% ✎	▂▂▂▃▂▂▁▃▄▆█▆ beats 39/246	very easy · avg 90%	▇▇▇ 8.0%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	24.1% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 48/246	medium · avg 46%	▇▇▇ 7.4%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	42.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 40/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	55.2% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 73/246	easy · avg 66%	▇▇ 6.1%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	73.8% ✎	▁▁▂▁▃▂▂▂▃▆█▅ beats 34/246	very easy · avg 96%	▇▇ 5.8%	sharp · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	72.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 98/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	35.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 95/246	medium · avg 45%	▇ 2.4%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	29.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 53/246	medium · avg 39%	▇ 2.3%	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	55.5% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 74/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	45.1% ✎	██▄▃▃▄▁▁···▁ beats 87/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	68.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 120/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	23.6% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 95/246	hard · avg 22%	▇ 0.8%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	17.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 148/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	15.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 205/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	39.6300 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 97/247	avg 41.206 points	▇▇ 4.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	13.7100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 47/247	avg 38.861 points	▇ 2.3%	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/vllm-sr ↗

$ 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		= 42.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	54.2%	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]	41.3%	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