Mica v0.5 4B

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Mica v0.5 4B is an open-weights decision model from akivet, released October 2026. Its published size is 4.66B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine mica-v0.5-4b; reported model Mica v0.5 4B. Type: full fine-tune; technique: autoregressive. Implementation: https://github.com/akivet/Mica/tree/4adbdd398d6e2a9ca0a63b1e3d3b49240f03cee5. 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.

58.1±1.3#127 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Mica v0.5 4B, out of 357 with a score.

#	model	score	where	RAM	released
127	Seb-9B v2 ironbcc	58±1	model files
128	JPT-35B-A3B kirp	58±1	model files
129	Mica v0.5 4B akivet	58±1	model files		2026-10
130	AJev lora7 (Gemma 4 12B) andyzhang232	58±1	model files
131	Winnow-12B (DecisionBench b6ac22b0) EldanRing	58±2	local	~16GB

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #117 of 250 · 7.1% of its score · 6 tests

Beats Senova-4B v2, Tern-35B-A3B, GEV-26B-Decide here, though they rank higher overall. Trails OneJev1.6-0.8B, TokenRhythm NeoHorse-Jev-4B, razorback16 diffgemma (decision readout) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: API-Bank (accuracy) submitted	85.8% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 186/236	easy · avg 70%	▇ 2.2%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	95.0% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 129/246	very easy · avg 92%	▇ 1.6%	sharp · maxed out · noisy
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	77.3% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 185/243	medium · avg 37%	▇ 1.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	88.0% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 195/246	easy · avg 72%	▇ 1.1%	noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.4% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 171/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.5% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #90 of 258 · 6.8% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, Decider 31B (NVFP4), Jev 1.13 here, though they rank higher overall. Trails Jev-Style 2B v4, Sieve 2B v3, StartLux-Decision v1.1 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	45.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 156/246	medium · avg 38%	▇ 2.6%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	55.4% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 158/246	medium · avg 47%	▇ 2.4%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	86.0% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 192/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	65.8% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 109/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.3% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 160/238	easy · avg 83%	▇ 0.4%	sharp · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	86.4% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 147/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	15.2% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #97 of 256 · 23% of its score · 9 tests

Beats Turion Jev 31B, FlexDM · Gemma-4-31B (decision readout), jev-brain · Gemma-4-31B (decision readout) here, though they rank higher overall. Trails Decider 4B, jiwo 4B v2, Sieve 4B here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ANLI (macro-F1) submitted	68.4% ✎	▁▂▃▅▅█▂····▁ beats 146/246	medium · avg 60%	▇▇ 5.4%	at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	78.1% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 129/246	easy · avg 74%	▇▇ 5.3%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	92.8% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 155/246	very easy · avg 85%	▇▇ 4.5%	sharp
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	55.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 163/246	medium · avg 44%	▇ 2.5%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	42.4% ✎	▁··▂▃▃▅▇█▇▃▃ beats 208/246	hard · avg 22%	▇ 1.3%	at its level · noisy
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	81.5% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 177/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	77.9% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 194/246	medium · avg 62%	▇ 1.0%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	78.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 158/246	easy · avg 66%	▇ 0.8%	at its level · noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	90.6% ✎	▁···▁▁▁▁▃▆█▃ beats 157/246	easy · avg 84%	▇ 0.6%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #107 of 247 · 10% of its score · 6 tests

Beats Bobcat 1.3 (31B), Nace.AI Drex v2.0 (35B-A3B), decisio 0.6.0 (Gemma 4 31B) (decision readout) here, though they rank higher overall. Trails vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B), Crivo-400M, 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: New Yorker (accuracy) submitted	69.5% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 149/246	medium · avg 61%	▇▇ 4.0%	at its level
Decision Index 0.4.1: Humicroedit (accuracy) submitted	61.4% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 132/246	medium · avg 60%	▇ 2.0%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	63.4% ✎	▁········▁▇█ beats 154/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	90.2% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 139/246	easy · avg 83%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: POP909-CL (accuracy) submitted	39.4% ✎	▄▅▅▃▆▅▃▅▃▅▃█ beats 160/237	hard · avg 21%	▇ 1.0%	sharp · at its level · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	39.5% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 56/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #118 of 263 · 44% of its score · 14 tests

Beats OneJev1.6-4B here, though they rank higher overall. Trails PurpleMIST-Flash-1.0, Jevfire Qwen3.8-27B (decision readout), JevK5 9B v0.3.3 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	57.0% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 144/246	medium · avg 46%	▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: MMLU (accuracy) submitted	76.9% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 131/246	easy · avg 70%	▇▇▇ 6.8%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	75.3% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 160/246	easy · avg 66%	▇▇▇ 6.3%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	54.3% ✎	▁··▄█▆▆▆▅▅▃▁ beats 146/246	medium · avg 45%	▇ 3.6%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	50.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 198/246	medium · avg 39%	▇ 3.4%	blunt · at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	93.8% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 121/246	very easy · avg 90%	▇ 3.2%	sharp · maxed out
Decision Index 0.4.1: WinoGrande (accuracy) submitted	83.3% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 147/246	easy · avg 78%	▇ 3.0%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	34.6% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 200/246	hard · avg 22%	▇ 1.6%	at its level

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	97.6% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 110/246	very easy · avg 96%	▇ 1.5%	sharp · maxed out · noisy
Decision Index 0.4.1: MuSR (accuracy) submitted	58.4% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 113/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	51.4% ✎	██▄▃▃▄▁▁···▁ beats 117/246	medium · avg 58%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: CLadder (accuracy) submitted	80.0% ✎	▁███▆▅▃▃▁▁▁▁ beats 174/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	17.5% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 142/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	13.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 166/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 8.8% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	51.8100 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 154/247	avg 41.206 points	▇▇ 5.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	41.5500 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 136/247	avg 38.861 points	▇ 3.1%	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/sky7350 ↗

$ 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		= 58.1

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.5%	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]	15.2%	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

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