Crivo-1B

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Crivo-1B is an open-weights decision model from tardellirs. Its published size is 1.03B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine crivo-1b; reported model Crivo-1B. 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.

42.5±1.1#251 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Crivo-1B, out of 357 with a score, then more from tardellirs.

#	model	score	where	RAM	released
251	openvons Qwen3-4B (decision readout) genai-craft	43±1	source code
252	Intelif Qwen3-4B UserMoonlight	43±1	model files
253	Crivo-1B tardellirs	43±1	model files
254	vLLM-SR d3-lite (0.8B) vLLM Semantic Router	42±1	local	~4.5GB
255	OneJev1.5-0.8B OmniJev	42±4	model files		2026-10-13
	more from tardellirs
279	Crivo-400M tardellirs	37±1	model files
301	Crivo-150M v2 tardellirs	32±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▁▃▁▁▁▂▃▄▆██▆ #138 of 250 · 8.8% of its score · 6 tests

Beats Cerno 4B v1.1, Trio-Spark DI (9B), Decider 35B-A3B here, though they rank higher overall. Trails Amber 0.4B 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	93.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 109/246	very easy · avg 92%	▇▇ 3.8%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	80.7% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 121/236	easy · avg 70%	▇ 2.5%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	80.6% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 145/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	64.0% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 118/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	87.5% ✎	█▁▁▃▄▄▆▄▃▂▁▃ beats 202/243	medium · avg 37%	▇ 0.6%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	67.5% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #150 of 258 · 5.4% of its score · 7 tests

Beats Quyet-1.0-Large, Decider chat · Qwen3.6-27B (decision readout), Solar Decide here, though they rank higher overall. Trails Amber 0.4B, Saina Helm 2 Omni (0.8B), jdi-ptr14-0.8b here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	36.5% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 78/246	medium · avg 38%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	49.5% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 104/246	medium · avg 47%	▇ 1.7%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	86.7% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 206/246	easy · avg 74%	▇ 0.6%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	93.0% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 177/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	51.8% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 55/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	91.3% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 202/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	52.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #144 of 256 · 24% of its score · 9 tests

Beats Solar Decide, JoshuaSP diffgemma (decision readout), PurpleMIST-Flash-1.0 here, though they rank higher overall. Trails Decider 2B 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	84.5% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 109/246	very easy · avg 85%	▇▇▇ 8.3%	sharp
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	67.1% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 65/246	easy · avg 74%	▇▇ 5.4%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	55.5% ✎	▁▂▃▅▅█▂····▁ beats 84/246	medium · avg 60%	▇▇ 4.6%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	55.1% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 160/246	medium · avg 44%	▇ 1.7%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	83.9% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 204/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	78.1% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 196/246	medium · avg 62%	▇ 0.9%	at its level
Decision Index 0.4.1: FinEntity (macro-F1) submitted	92.0% ✎	▁···▁▁▁▁▃▆█▃ beats 179/246	easy · avg 84%	▇ 0.8%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	76.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 135/246	easy · avg 66%	▇ 0.7%	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	35.0% ✎	▁··▂▃▃▅▇█▇▃▃ beats 183/246	hard · avg 22%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #59 of 247 · 8.1% of its score · 6 tests

Beats OneJev1.6-27B, mogan-decision-31B-it, Cerno 27B 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	67.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 139/246	medium · avg 61%	▇ 3.5%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	54.3% ✎	▁·▁▃▃▂▅█▄▂▁▁ beats 52/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	94.9% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 188/246	easy · avg 83%	▇ 1.5%	sharp · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	51.1% ✎	▁········▁▇█ beats 28/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 29/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.6% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 75/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▃▂▃▃▅▅▆█▂ #216 of 263 · 47% of its score · 14 tests

Trails laya (DecisionBench 1c5edc17), LFM2.5-2.6B-RLCD, Kodiak v0.2 1B (accuracy) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	66.1% ✎	▂▂▂▂▃▂▁▃▄▆█▆ beats 47/246	very easy · avg 90%	▇▇▇ 7.9%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	20.7% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 41/246	medium · avg 46%	▇▇▇ 7.5%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	44.7% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 44/246	easy · avg 70%	▇▇▇ 7.3%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	43.1% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 45/246	easy · avg 66%	▇▇ 6.1%	at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	82.8% ✎	▁▁▂▁▂▃▂▂▃▆█▅ beats 48/246	very easy · avg 96%	▇▇ 5.6%	sharp · noisy
Decision Index 0.4.1: WinoGrande (accuracy) submitted	75.5% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 112/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	20.2% ✎	▁··▄█▆▆▆▅▅▃▁ beats 38/246	medium · avg 45%	▇ 2.5%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	26.0% ✎	▂▆▅▅▆█▆▃▁··▁ beats 27/246	medium · avg 39%	▇ 2.3%	blunt · at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	62.8% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 156/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	33.7% ✎	██▄▃▃▄▁▁···▁ beats 16/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	82.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 188/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	16.6% ✎	▁▁▁▁▁▁▁▃▅█▂▁ beats 60/246	hard · avg 22%	▇ 0.8%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	7.2% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 6/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	15.0% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 199/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.5% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	38.1500 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 89/247	avg 41.206 points	▇▇ 4.2%	blunt
Decision Index 0.4.1: private new domains (equated points)	15.9200 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 61/247	avg 38.861 points	▇ 2.3%	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 99%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 42.5

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	67.5%	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]	52.9%	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