Mola-150M

+ contribute

Mola-150M is an open-weights decision model from codavidgarcia, released 14 October 2026. Its published size is 0.15B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine mola-150m; reported model Mola-150M. 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.

32.6±1.0#293 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Mola-150M, out of 357 with a score, then more from codavidgarcia.

#	model	score	where	RAM	released
293	jevhome-E (JevBench mini) Jibril Frej	33±2	source code
294	vLLM-SR d3-edge (0.6B) vLLM Semantic Router	33±1	local	~2.6GB
295	Mola-150M codavidgarcia	33±1	model files		2026-10-14
296	DM-JEPA 1.1 Danger Labs	33±1	model files
297	Laya (english) (JevBench mini) Convai Innovations	33±2	source code
	more from codavidgarcia
318	Mola-68M codavidgarcia	29±1	model files		2026-10-14

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #171 of 250 · 10% of its score · 6 tests

Beats LiquidAI d1-3B, Decider 4B, Together Tev1 Qwen3.5-4B 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	91.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 79/246	very easy · avg 92%	▇▇ 5.5%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	42.1% ✎	▁▁▁▁▁▁▁▃▃▂█▂ beats 35/236	easy · avg 70%	▇ 2.1%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	74.4% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 110/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	57.1% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 50/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 12/243	medium · avg 37%	▇ 0.2%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	56.1% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #165 of 258 · 4.7% of its score · 7 tests

Beats Solar Decide, decisio 0.4.0 (Qwen3.6-35B-A3B) (decision readout), JevK5 9B v0.3.3 here, though they rank higher overall. Trails Bosun v3.1 1.7B LoRA, Dinah-1, DecisionTune 1.0 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	46.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 91/246	medium · avg 47%	▇ 1.4%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	28.3% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 40/246	medium · avg 38%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	89.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 118/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	84.9% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 182/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.1% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 26/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	88.7% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 168/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	68.0% ✎	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▂▂▃▃▂▅▆▃█▆▄▃ #222 of 256 · 24% of its score · 9 tests

Beats wyat-1-800m, Valen-0.8B, JPT-0.8B Qwen3.5-0.8B LoRA here, though they rank higher overall. Trails JEV Ettin 400M, LiquidAI d1-omni-600M, Dinah-1 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	51.5% ✎	▂▄▃▂▄▇▃▇█▅▃▁ beats 34/246	very easy · avg 85%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	57.0% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 33/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	38.6% ✎	▁▂▃▅▅█▂····▁ beats 34/246	medium · avg 60%	▇▇ 3.9%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	28.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 51/246	medium · avg 44%	▇ 1.2%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	78.1% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 143/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	71.9% ✎	▁···▁▁▁▁▃▆█▃ beats 46/246	easy · avg 84%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	74.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 170/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	53.1% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 61/246	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	19.9% ✎	▁··▂▃▃▅▇█▇▃▃ beats 108/246	hard · avg 22%	▇ 0.4%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #217 of 247 · 7.3% 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	42.2% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 42/246	medium · avg 61%	▇ 3.0%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	51.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 30/246	easy · avg 83%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	55.7% ✎	▁·▁▃▂▃▅█▄▂▁▁ beats 65/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	47.8% ✎	▁········▃▇█ beats 2/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.8% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 80/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	3.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 61/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▃▂▂▃▃▅▅▆█▂ #232 of 263 · 48% of its score · 14 tests

Beats Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326), Amber 0.4B, vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B) here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), LFM2.5-2.6B-RLCD, Jev-Style 0.8B v3 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	70.2% ✎	▁▁▂▃▂▂▂▂▃▆█▅ beats 29/246	very easy · avg 96%	▇▇▇▇ 11%	sharp · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	53.8% ✎	▂▂▂▃▂▂▁▃▄▆█▆ beats 34/246	very easy · avg 90%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	38.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 29/246	easy · avg 70%	▇▇▇ 6.7%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	36.8% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 22/246	easy · avg 66%	▇▇ 5.3%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	17.3% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 29/246	medium · avg 46%	▇▇ 5.1%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	60.1% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 45/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	19.9% ✎	▃▆▅▅▆█▆▃▁··▁ beats 0/246	medium · avg 39%	▇ 1.8%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	23.0% ✎	▁··▄█▆▆▆▅▅▃▁ beats 49/246	medium · avg 45%	▇ 1.6%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	55.7% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 77/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	72.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 139/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	44.7% ✎	██▄▃▃▄▁▁···▁ beats 84/246	medium · avg 58%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	8.7% ✎	▁▁▁▁▁▁▃▂▅█▂▁ beats 41/246	hard · avg 22%	▇ 0.5%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	8.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 30/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	16.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 221/246	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)	22.7700 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 45/247	avg 41.206 points	▇ 3.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	10.4500 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 20/247	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		= 32.6

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	56.1%	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]	68.0%	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