Crivo-150M v2

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Crivo-150M v2 is an open-weights decision model from tardellirs. Its published size is 0.15B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine crivo-150m-v2; reported model Crivo-150M v2. 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.

31.8±1.0#299 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Crivo-150M v2, out of 357 with a score, then more from tardellirs.

#	model	score	where	released
299	JEV FLAN-T5 Large public v2 (342M) Elfsong	32±1	model files	2026-10-18
300	Verdict 1.4 (JevBench mini) Heman10x	32±2	source code
301	Crivo-150M v2 tardellirs	32±1	model files
302	Bekko System One v0 400M hotchpotch	32±1	model files
303	vera-spark scar-ai	31±1	model files
	more from tardellirs
253	Crivo-1B tardellirs	43±1	model files
279	Crivo-400M tardellirs	37±1	model files
312	Crivo-68M tardellirs	30±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▃▃▄▆██▆ #210 of 250 · 10% of its score · 6 tests

Beats Cam1, InternLM Intern-Decision Qwen3.5-2B, JEV Ettin 150M here, though they rank higher overall. Trails JevK5 Lite, Crivo-32M v2, Mola-68M 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	76.3% ✎	▁▂▁▁▁▃▂▄▅▆█▁ beats 39/246	very easy · avg 92%	▇▇ 5.7%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	70.7% ✎	▁▁▁▁▁▁▁▂▃▃█▂ beats 90/236	easy · avg 70%	▇ 2.1%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	64.4% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 77/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	62.8% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 100/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	63.6% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 154/243	medium · avg 37%	▇ 0.2%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	68.7% ✎	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▁▁▁·▁▁▁▃▃▃█▅ #205 of 258 · 4.6% of its score · 7 tests

Beats SemIf Qwen3.5-4B Base (decision readout), Metask-Jev-4B, Jobe Qwen3.5-4B (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: Amazon ESCI (macro-F1) submitted	37.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 52/246	medium · avg 47%	▇ 1.4%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	31.0% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 53/246	medium · avg 38%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	89.5% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 119/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	80.2% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 145/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 23/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	85.8% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 140/238	easy · avg 79%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	20.1% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #220 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, 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: HellaSwag (accuracy) submitted	54.3% ✎	▂▄▃▂▄▇▃▇█▅▃▁ beats 36/246	very easy · avg 85%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	57.4% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 35/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	38.3% ✎	▁▂▃▅▅█▂····▁ beats 32/246	medium · avg 60%	▇▇ 3.9%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	1.9% ✎	▁·▃·▁▁▂▄▅█▇▄ beats 2/246	medium · avg 44%	▇ 1.2%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	80.3% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 166/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	85.4% ✎	▁···▁▁▁▁▃▆█▃ beats 102/246	easy · avg 84%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	72.3% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 149/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	63.1% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 73/246	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	22.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 121/246	hard · avg 22%	▇ 0.4%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #135 of 247 · 7.2% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5, Cerno 4B v1.1 here, though they rank higher overall. Trails Crivo-68M 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	54.7% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 72/246	medium · avg 61%	▇ 3.0%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	86.5% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 113/246	easy · avg 83%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	50.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 22/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	49.2% ✎	▁········▁▇█ beats 7/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.1% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 52/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	2.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 45/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▃▂▂▃▃▅▅▆█▂ #238 of 263 · 49% of its score · 14 tests

Beats Amber 0.4B 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	66.5% ✎	▁▁▂▃▂▂▂▂▃▆█▅ beats 26/246	very easy · avg 96%	▇▇▇▇ 11%	sharp · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	40.7% ✎	▂▃▂▂▂▂▁▃▄▆█▆ beats 18/246	very easy · avg 90%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	36.1% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 24/246	easy · avg 70%	▇▇▇ 6.6%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	36.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 21/246	easy · avg 66%	▇▇ 5.3%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	14.9% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 20/246	medium · avg 46%	▇▇ 5.0%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	54.7% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 29/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	26.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 26/246	medium · avg 39%	▇ 1.8%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	18.5% ✎	▁··▄█▆▆▆▅▅▃▁ beats 20/246	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	50.4% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 34/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	66.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 101/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	45.8% ✎	██▄▃▃▄▁▁···▁ beats 92/246	medium · avg 58%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	3.9% ✎	▁▁▁▁▃▁▁▂▅█▂▁ beats 29/246	hard · avg 22%	▇ 0.5%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	8.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 24/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	16.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 226/246	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)	24.1600 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 49/247	avg 41.206 points	▇ 3.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	9.4100 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 18/247	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/tardellirs ↗

$ 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		= 31.8

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	68.7%	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]	20.1%	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

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