Crivo-68M

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Crivo-68M is an open-weights decision model from tardellirs. Its published size is 0.07B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine crivo-68m; reported model Crivo-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

· Weights licence ↗ · Parameter count ↗

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

29.7±1.0#310 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

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

#	model	score	where	RAM
310	InternLM Intern-Decision Qwen3.5-0.8B Shanghai AI Laboratory (InternLM)	30±1	model files
311	OpenDecision (DecisionBench a51e07b5) deepanwadhwa	30±2	model files
312	Crivo-68M tardellirs	30±1	model files
313	GLiNER2.5-Decide (DecisionBench 0872ab14) Fastino	30±2	model files
314	LiquidAI d1-omni-600M Liquid AI	30±1	local	~2.7GB
	more from tardellirs
253	Crivo-1B tardellirs	43±1	model files
279	Crivo-400M tardellirs	37±1	model files
301	Crivo-150M v2 tardellirs	32±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #198 of 250 · 10% of its score · 6 tests

Beats Cam1, mini-jev Qwen3-4B (decision readout), FLock this-that 1.2 here, though they rank higher overall. Trails JevK5 Lite, 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	82.5% ✎	▁▂▁▁▁▂▃▄▅▆█▁ beats 51/246	very easy · avg 92%	▇▇ 6.0%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	60.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 69/236	easy · avg 70%	▇ 2.0%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	65.3% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 80/246	easy · avg 72%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	60.0% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 63/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	75.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 182/243	medium · avg 37%	▇ 0.2%	sharp · too hard for it · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	57.0% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #193 of 258 · 4.6% of its score · 7 tests

Beats JevK5 9B v0.3.3, Hopper (G) 1.2 Qwen3.5-4B LoRA, Solar Decide Flash 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	40.8% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 64/246	medium · avg 47%	▇ 1.3%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	30.1% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 50/246	medium · avg 38%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	87.6% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 99/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	81.4% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 158/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.2% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 31/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	86.0% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 141/238	easy · avg 79%	▇ 0.4%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	45.8% ✎	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▂▃▂▃▂▅▆▃█▆▄▃ #237 of 256 · 23% of its score · 9 tests

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	39.3% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 19/246	very easy · avg 85%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	55.2% ✎	▁▁▁▂▃▃▃▄▇▇█▄ beats 27/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	36.0% ✎	▁▂▃▅▅█▂····▁ beats 26/246	medium · avg 60%	▇▇ 3.8%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	0.0% ✎	▃·▁·▁▁▂▄▅█▇▄ beats 1/246	medium · avg 44%	▇ 1.1%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	79.8% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 163/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	85.3% ✎	▁···▁▁▁▁▃▆█▃ beats 101/246	easy · avg 84%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	69.5% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 134/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	64.4% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 76/246	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 122/246	hard · avg 22%	▇ 0.3%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #134 of 247 · 7.1% of its score · 6 tests

Beats OneJev1.6-4B, Nace.AI Drex v1.5, Cerno 4B v1.1 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	51.1% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 60/246	medium · avg 61%	▇ 2.9%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	86.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 115/246	easy · avg 83%	▇ 1.8%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	49.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 16/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	49.7% ✎	▁········▁▇█ beats 11/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.6% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 58/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 28/237	hard · avg 21%	▇ 0.1%	sharp · too hard for it · noisy

knowledge & reasoning▁▃▂▂▂▃▃▅▅▆█▂ #248 of 263 · 49% of its score · 14 tests

Beats Amber 0.4B, Dinah-1 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	58.3% ✎	▁▁▃▁▂▂▂▂▃▆█▅ beats 21/246	very easy · avg 96%	▇▇▇▇▇ 12%	sharp · at its level · noisy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	36.2% ✎	▂▃▂▂▂▂▁▃▄▆█▆ beats 13/246	very easy · avg 90%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	32.6% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 14/246	easy · avg 70%	▇▇▇ 6.4%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	35.2% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 18/246	easy · avg 66%	▇▇ 5.1%	at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	14.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 16/246	medium · avg 46%	▇▇ 4.6%	sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted	53.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 24/246	easy · avg 78%	▇ 3.6%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	25.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 17/246	medium · avg 39%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	17.7% ✎	▁··▄█▆▆▆▅▅▃▁ beats 8/246	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	49.7% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 29/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	54.0% ✎	▁███▆▅▃▃▁▁▁▁ beats 34/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	44.7% ✎	██▄▃▃▄▁▁···▁ beats 85/246	medium · avg 58%	▇ 0.7%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	0.7% ✎	▃▁▁▁▁▁▁▂▅█▂▁ beats 12/246	hard · avg 22%	▇ 0.4%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	7.3% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 7/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	15.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 209/246	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)	24.5100 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 51/247	avg 41.206 points	▇ 3.6%	blunt
Decision Index 0.4.1: private new domains (equated points)	12.0200 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 34/247	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		= 29.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	57.0%	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]	45.8%	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