Cam1

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Cam1 is an open-weights decision model from cbuk10001. Its published size is 4.66B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine cam1; reported model Cam1. Type: LoRA + head; 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.

41.7±1.1#256 of 355 decision modelsfrom 41 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Cam1, out of 357 with a score.

#	model	score	where
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
260	Qwen3-Reranker-4B (DecisionBench 22e68366) Alibaba (Qwen)	41±2	model files

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

$ what it's good at

tools & automation▁▃▁▁▃▂▃▄▆██▆ #219 of 250 · 8.9% of its score · 6 tests

Trails Prumo (rule-based engine), JevK5 Lite, 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: BFCL (case exact accuracy) submitted	68.9% ✎	▁▂▁▁▃▂▂▄▅▆█▁ beats 30/246	very easy · avg 92%	▇▇ 3.9%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	65.0% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 79/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	58.9% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 64/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	59.1% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 59/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	8.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 65/243	medium · avg 37%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	78.5% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #201 of 258 · 4.8% of its score · 6 tests

Beats Solar Decide Flash, Ryotide Qwen v0.3.1 (decision readout), SemIf Qwen3.5-4B Base (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	29.2% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 45/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	39.5% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 56/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	61.9% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 62/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	79.1% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 62/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	76.7% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 70/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	65.9% ✎	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▂▂▂▃▃▅▆▃█▆▄▃ #196 of 256 · 24% of its score · 9 tests

Beats Solar Decide Flash, 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	73.9% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 59/246	very easy · avg 85%	▇▇▇ 8.5%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	64.4% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 57/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	53.1% ✎	▁▂▃▅▅█▂····▁ beats 77/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	38.8% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 86/246	medium · avg 44%	▇ 1.6%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	63.2% ✎	▁▁▁▁▁▁▁▂▃▇▇█ beats 53/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	52.1% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 82/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	83.7% ✎	▁···▁▁▁▁▃▆█▃ beats 92/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	13.4% ✎	▁▁▁▁▁▃▁▁▁▃▆█ beats 16/246	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	4.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 20/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #216 of 247 · 8.0% of its score · 6 tests

Beats Valen-4B, TokenRhythm NeoHorse-Jev-4B, OneJev1.6-0.8B here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Bekko System One v0 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	49.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 57/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	51.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 29/246	easy · avg 83%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	51.1% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 29/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	55.4% ✎	▁········▁▇█ beats 53/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	8.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 99/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	35.3% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 18/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #177 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.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	88.3% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 83/246	very easy · avg 90%	▇▇▇ 8.2%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	42.6% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 88/246	medium · avg 46%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	67.3% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 87/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	60.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 82/246	easy · avg 66%	▇▇ 6.1%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	95.8% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 87/246	very easy · avg 96%	▇▇ 6.0%	sharp · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	63.3% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 55/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	26.4% ✎	▁··▄█▆▆▆▅▅▃▁ beats 62/246	medium · avg 45%	▇ 2.4%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	33.7% ✎	▂▆▅▅▆█▆▃▁··▁ beats 79/246	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	56.3% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 85/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	44.7% ✎	██▄▃▃▄▁▁···▁ beats 86/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	56.9% ✎	▁███▆▅▃▃▁▁▁▁ beats 54/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	22.8% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 88/246	hard · avg 22%	▇ 0.8%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	10.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 63/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 107/246	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)	31.6000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 70/247	avg 41.206 points	▇▇ 4.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	38.4900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 117/247	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/cbuk10001 ↗

$ 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	41	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 41.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	78.5%	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]	65.9%	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