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Bekko System One v0 68M

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Bekko System One v0 68M is an open-weights decision model from hotchpotch. Its published size is 0.07B parameters.

Catalogue identity notes

Exact Decision Index tested engine bekko-v0-68m; reported model Bekko System One v0 68M. 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

· Parameter count ↗

Publisher parameter count (estimated by publisher); includes the served backbone, not just adapter size.

23.5±1.0#332 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Bekko System One v0 68M, out of 357 with a score, then more from hotchpotch.

#	model	score	where
332	kev-0.5b (DecisionBench 9ce2fd39) Jared Palmer	24±2	model files
333	Crivo-17M tardellirs	24±1	model files
334	Bekko System One v0 68M hotchpotch	24±1	model files
335	MoganAI Lavoir ModernBERT-large Mogan AI	24±1	model files
336	GLiNER2.5-Decide Fastino	23±1	model files
	more from hotchpotch
302	Bekko System One v0 400M hotchpotch	32±1	model files
347	Bekko System One v0 17M hotchpotch	19±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #243 of 250 · 10% of its score · 6 tests

Beats Von 1.3 here, though they rank higher overall. Trails LFM2.5-350M-RLCD, CLM-v0.1-8B Qwen3-8B heads, Verdict 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	37.4% ✎	▁▃▁▁▁▂▂▄▅▆█▁ beats 6/246	very easy · avg 92%	▇▇▇ 6.7%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	2.6% ✎	▁▁▃▁▁▁▁▂▃▂█▂ beats 7/236	easy · avg 70%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	37.4% ✎	▁▁▁▃▃▅▅▆█▇█▃ beats 22/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	48.6% ✎	▁▁▁▁▁·▁▃▁▄█▁ beats 29/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 1/243	medium · avg 37%	▇ 0.1%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	51.8% ✎	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▁▁▁·▁▁▃▁▃▃█▅ #234 of 258 · 4.5% of its score · 7 tests

Beats Sieve 2B, Strands Decider 2B (Hobson v21), DM-JEPA 1.1 here, though they rank higher overall. Trails 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: Amazon ESCI (macro-F1) submitted	27.1% ✎	▁▁▁▁▁▁▃▂▃▃█▅ beats 24/246	medium · avg 47%	▇ 1.2%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	21.5% ✎	▁▁▁▁▁▃▁▂▂▄▇█ beats 23/246	medium · avg 38%	▇ 1.2%	blunt
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	76.4% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 53/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	56.6% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 31/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	47.7% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 5/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	71.8% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 47/238	easy · avg 79%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	47.0% ✎	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▂▃▂▃▂▅▆▃█▆▄▃ #240 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	36.6% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 16/246	very easy · avg 85%	▇▇▇▇ 9.4%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	48.5% ✎	▁▁▁▃▂▃▃▄▇▇█▄ beats 12/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	31.7% ✎	▁▃▃▅▅█▂····▁ beats 20/246	medium · avg 60%	▇ 3.5%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	45.9% ✎	▁···▁▁▃▁▃▆█▃ beats 15/246	easy · avg 84%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	26.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 44/246	medium · avg 44%	▇ 1.0%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	41.9% ✎	▁▁▁▁▁▃▁▂▂▇▇█ beats 25/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	32.5% ✎	▁▁▁▃▅▄▄▂▄▆█▄ beats 9/246	medium · avg 62%	▇ 0.7%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	1.4% ✎	▁▃▁▁▁▁▁▁▁▃▆█ beats 5/246	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	4.2% ✎	▁··▂▃▃▅▇█▇▃▃ beats 21/246	hard · avg 22%	▇ 0.2%	too hard for it · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #174 of 247 · 7.0% of its score · 6 tests

Beats Sieve 9B, Kev 9B v2, vLLM-SR d3-nano (2B) here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: New Yorker (accuracy) submitted	33.0% ✎	▁▁▃▃▃▃▇▅█▅▃▁ beats 22/246	medium · avg 61%	▇ 2.7%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	73.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 75/246	easy · avg 83%	▇ 1.9%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	46.0% ✎	▁·▃▃▂▂▅█▄▂▁▁ beats 1/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	49.6% ✎	▁········▁▇█ beats 9/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	33.7% ✎	▁▃▄█▇▅▁▁▄▄▁▁ beats 12/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	8.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 97/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▃▂▂▂▃▃▅▅▆█▂ #247 of 263 · 49% of its score · 14 tests

Beats Amber 0.4B, Dinah-1, Crivo-68M 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: ARC-Easy (accuracy) submitted	57.0% ✎	▁▁▃▁▂▂▂▂▃▆█▅ beats 18/246	very easy · avg 96%	▇▇▇▇▇▇ 15%	sharp · at its level · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	37.5% ✎	▂▃▂▂▂▂▁▃▄▆█▆ beats 16/246	very easy · avg 90%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	32.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 15/246	easy · avg 70%	▇▇ 5.9%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	33.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 8/246	easy · avg 66%	▇▇ 4.8%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	52.3% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 22/246	easy · avg 78%	▇ 3.7%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	16.5% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 26/246	medium · avg 46%	▇ 3.7%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	25.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 19/246	medium · avg 39%	▇ 1.6%	blunt
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	20.6% ✎	▁··▄█▆▆▆▅▅▃▁ beats 41/246	medium · avg 45%	▇ 1.1%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	52.9% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 45/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	50.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 19/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	37.4% ✎	██▄▃▃▄▁▁···▁ beats 36/246	medium · avg 58%	▇ 0.7%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	0.0% ✎	▃▁▁▁▁▁▁▂▅█▂▁ beats 2/246	hard · avg 22%	▇ 0.4%	too hard for it
Decision Index 0.4.1: ChessBench (accuracy) submitted	7.8% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 18/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	15.6% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 210/246	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)	11.7200 points ✎	▂▃▂▃▃▃▄▅▅▇█▃ beats 16/247	avg 41.206 points	▇ 3.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	13.4300 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 45/247	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/hotchpotch ↗

$ 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		= 23.5

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	51.8%	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]	47.0%	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