Mola-68M

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Mola-68M is an open-weights decision model from codavidgarcia, released 14 October 2026. Its published size is 0.07B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine mola-68m; reported model Mola-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

Release date ↗ · Weights licence ↗ · Parameter count ↗

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

28.9±1.0#316 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Mola-68M, out of 357 with a score, then more from codavidgarcia.

#	model	score	where	RAM	released
316	Bosun v3.1 1.7B LoRA Hanno Labs	29±1	model files
317	vLLM-SR Decision 2.0 Kai 0.6B vLLM Semantic Router	29±1	local	~3.7GB
318	Mola-68M codavidgarcia	29±1	model files		2026-10-14
319	JEV Ettin 400M Elfsong	29±1	model files
320	ZTC-Judge-4B (DecisionBench b0bb1603) FINAL-Bench	29±2	model files
	more from codavidgarcia
295	Mola-150M codavidgarcia	33±1	model files		2026-10-14

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #180 of 250 · 10% of its score · 6 tests

Beats Decider 4B, JevK5 v0.3, FlyMy.AI Decision 4B v1.6 here, though they rank higher overall. Trails JevK5 Lite 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	89.4% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 69/246	very easy · avg 92%	▇▇ 6.1%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	46.1% ✎	▁▁▁▁▁▁▁▃▃▂█▂ beats 40/236	easy · avg 70%	▇ 1.9%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	67.6% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 88/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	52.8% ✎	▁▁▁▁▁·▁▁▃▄█▁ beats 36/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 11/243	medium · avg 37%	▇ 0.2%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	53.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #172 of 258 · 4.5% of its score · 7 tests

Beats Solar Decide, JevK5 9B v0.3.3, vLLM-SR Decision 2.0 Lux 9B here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	45.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 84/246	medium · avg 47%	▇ 1.3%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	20.5% ✎	▁▁▁▁▁▃▁▂▂▄▇█ beats 20/246	medium · avg 38%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	87.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 97/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	83.5% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 173/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	52.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 59/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	87.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 160/238	easy · avg 79%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	66.1% ✎	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▂▃▂▃▂▅▆▃█▆▄▃ #238 of 256 · 23% of its score · 9 tests

Beats Bosun v3.1 1.7B LoRA 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	37.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 18/246	very easy · avg 85%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	49.5% ✎	▁▁▁▃▂▃▃▄▇▇█▄ beats 17/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	35.4% ✎	▁▂▃▅▅█▂····▁ beats 25/246	medium · avg 60%	▇ 3.7%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	28.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 50/246	medium · avg 44%	▇ 1.1%	typical
Decision Index 0.4.1: FinEntity (macro-F1) submitted	72.3% ✎	▁···▁▁▁▁▃▆█▃ beats 47/246	easy · avg 84%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	74.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 108/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	71.6% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 145/246	medium · avg 62%	▇ 0.7%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	51.8% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 54/246	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	10.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 56/246	hard · avg 22%	▇ 0.3%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #237 of 247 · 7.1% of its score · 6 tests

Beats JEV Ettin 150M, JEV FLAN-T5 Large public v2 (342M), Kev 0.8B r15 here, though they rank higher overall. Trails Zev (decision readout), LFM2.5-350M-RLCD, Nirnaya 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	30.1% ✎	▁▁▃▃▃▃▇▅█▅▃▁ beats 18/246	medium · avg 61%	▇ 2.9%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	48.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 10/246	easy · avg 83%	▇ 1.8%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	51.3% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 35/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	49.5% ✎	▁········▁▇█ beats 8/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.0% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 49/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	7.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 86/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▃▂▂▃▃▅▅▆█▂ #240 of 263 · 49% of its score · 14 tests

Beats Amber 0.4B, DecisionTune 1.0, Dinah-1 here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), JevK5 Lite, LFM2.5-2.6B-RLCD 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	61.0% ✎	▁▁▃▁▂▂▂▂▃▆█▅ beats 23/246	very easy · avg 96%	▇▇▇▇▇ 13%	sharp · at its level · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	45.1% ✎	▂▂▃▂▂▂▁▃▄▆█▆ beats 26/246	very easy · avg 90%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	33.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 17/246	easy · avg 70%	▇▇▇ 6.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	35.0% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 16/246	easy · avg 66%	▇▇ 5.1%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	14.1% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 15/246	medium · avg 46%	▇▇ 4.4%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	54.8% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 30/246	easy · avg 78%	▇ 3.6%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	26.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 32/246	medium · avg 39%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	23.1% ✎	▁··▄█▆▆▆▅▅▃▁ beats 51/246	medium · avg 45%	▇ 1.4%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	50.4% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 33/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	64.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 91/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	44.0% ✎	██▄▃▃▄▁▁···▁ beats 80/246	medium · avg 58%	▇ 0.7%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	3.6% ✎	▁▁▁▁▃▁▁▂▅█▂▁ beats 28/246	hard · avg 22%	▇ 0.4%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	6.9% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 2/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	15.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 202/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 5.6% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	21.2000 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 39/247	avg 41.206 points	▇ 3.6%	blunt
Decision Index 0.4.1: private new domains (equated points)	12.2000 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 35/247	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/codavidgarcia ↗

$ 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		= 28.9

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	53.0%	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]	66.1%	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

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data updated 2026-11-03 02:37 UTC · sources and licences · json