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Amos 1 Large (27B)

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Amos 1 Large (27B) is an open-weights decision model from mukaddamzaid, released 30 September 2026. Its published size is 27.78B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine amos-1-large; reported model Amos 1 Large (27B). Type: full fine-tune; technique: autoregressive. 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.

68.7±1.2#26 of 355 decision modelsfrom 56 benchmark results across 3 sources

$ how it compares

The decision models ranked either side of Amos 1 Large (27B), out of 357 with a score.

#	model	score	where	released
24	baselabs elephant-1 (9B) baselabs	69±1	model files	2026-10-21
25	vLLM-SR d3 (27B) vLLM Semantic Router	69±1	model files
26	Amos 1 Large (27B) mukaddamzaid	69±1	model files	2026-09-30
27	AJev lm6q (Gemma 4 31B) andyzhang232	69±2	model files
28	AnyJev Tacitus 31B morriszjm	69±2	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #22 of 250 · 3.8% of its score · 6 tests

Beats Jeffan-31b-1710, Fastino GLiDE 1.2, KnowLine 31B Gen1 here, though they rank higher overall. Trails Solomon v1.1, Clef-flash, Clef-omni 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	86.0% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 194/236	easy · avg 70%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	68.9% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 218/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	81.8% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 200/243	medium · avg 37%	▇ 0.7%	sharp · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	71.8% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 101/246	easy · avg 72%	▇ 0.6%	noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	97.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 228/246	very easy · avg 92%	▇ 0.6%	sharp · maxed out · noisy
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▁▁▁·▁▁▁▁▃▃█▅ #17 of 258 · 5.5% of its score · 7 tests

Beats Fastino GLiDE 1.2, KnowLine 31B Gen1, Ainvest-Decision-27B v1.0 here, though they rank higher overall. Trails StartLux-Decision v1.1 4B, VisionJEV 1.0.0 (27B), OneShot 27B 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	50.1% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 233/246	medium · avg 38%	▇ 2.3%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	62.1% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 234/246	medium · avg 47%	▇ 2.0%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	77.4% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 132/246	easy · avg 74%	▇ 0.4%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	78.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 165/245	easy · avg 70%	▇ 0.4%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	88.9% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 169/238	easy · avg 79%	▇ 0.2%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	94.8% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 203/238	easy · avg 83%	▇ 0.2%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	11.8% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #20 of 256 · 15% of its score · 9 tests

Beats KnowLine 31B Gen1, Ainvest-Decision-27B v1.0, WeMM-JEV-27B here, though they rank higher overall. Trails Clef-flash, Clef-omni, Clef 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	77.8% ✎	▁▂▃▅▅█▂····▁ beats 222/246	medium · avg 60%	▇▇ 3.8%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	86.8% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 237/246	easy · avg 74%	▇ 3.5%	typical
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	73.3% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 242/246	medium · avg 44%	▇ 2.0%	at its level
Decision Index 0.4.1: HellaSwag (accuracy) submitted	97.3% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 229/246	very easy · avg 85%	▇ 1.8%	sharp · maxed out
Decision Index 0.4.1: ACOS (per-review F1) submitted	45.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 214/246	hard · avg 22%	▇ 1.3%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	78.2% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 200/246	medium · avg 62%	▇ 0.8%	typical
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	84.7% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 223/246	easy · avg 71%	▇ 0.7%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	83.3% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 211/246	easy · avg 66%	▇ 0.5%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	94.2% ✎	▁···▁▁▁▁▃▆█▃ beats 219/246	easy · avg 84%	▇ 0.3%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #29 of 247 · 7.1% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), WeMM-JEV-27B here, though they rank higher overall. Trails Kas 4B, Clef-omni, Clef 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	75.4% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 195/246	medium · avg 61%	▇ 2.7%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	66.5% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 221/246	medium · avg 60%	▇ 1.7%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	65.0% ✎	▁········▁▇█ beats 180/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	57.0% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 173/237	hard · avg 21%	▇ 0.9%	sharp · at its level · noisy
Decision Index 0.4.1: BPoMP (accuracy) submitted	96.7% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 217/246	easy · avg 83%	▇ 0.6%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.0% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 65/246	medium · avg 47%	▇ 0.3%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #37 of 263 · 41% of its score · 15 tests

Beats vera-large, KnowLine 26B-A4B Gen2.5, OneJev1.6-27B here, though they rank higher overall. Trails Solar Decide, Clef-omni, GPT-6 Luna Decisions here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Etsabary · 1342 text decisions	80.0% ✎	▁··▂·▃▅▁▃▂▃█ beats 16/24	medium · avg 47%	▇▇▇▇▇ 12%	sharp
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	68.0% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 197/246	medium · avg 46%	▇▇▇ 7.7%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	87.9% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 226/246	easy · avg 66%	▇▇ 3.9%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	87.7% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 217/246	easy · avg 70%	▇▇ 3.8%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	56.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 239/246	medium · avg 39%	▇ 3.0%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	75.0% ✎	▁··▄█▆▆▆▅▅▃▁ beats 204/246	medium · avg 45%	▇ 2.5%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	93.5% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 220/246	easy · avg 78%	▇ 1.8%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	29.8% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 142/246	hard · avg 22%	▇ 1.6%	at its level

7 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	97.4% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 221/246	very easy · avg 90%	▇ 1.1%	sharp · maxed out
Decision Index 0.4.1: MuSR (accuracy) submitted	66.8% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 199/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	86.8% ✎	██▄▃▃▄▁▁···▁ beats 230/246	medium · avg 58%	▇ 0.8%	noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	19.0% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 161/246	hard · avg 16%	▇ 0.7%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	80.5% ✎	▁███▆▅▃▃▁▁▁▁ beats 179/246	easy · avg 71%	▇ 0.7%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.1% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 205/246	very easy · avg 96%	▇ 0.4%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	12.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 140/246	very hard · avg 13%	▇ 0.0%	blunt

vision▁·▃▂▃▃▇▄▄█▄▃ #7 of 79 · 20% of its score · 13 tests

Beats Fastino GLiDE 1.2, StartLux-Decision v1.1 27B, vLLM-SR d3-ultra (Decision 3.0, 27B) here, though they rank higher overall. Trails Mercury Decide (free endpoint), Jev 1.14, Jev 1.13 here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
Etsabary · 200 image decisions	79.5% ✎	▂▂··▂▃▂·█▃▂▃ beats 14/14	medium · avg 45%	▇▇▇ 8.6%	sharp · at its level
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted	82.1900 points ✎	▁·▁▁▃▁▄▄▃▅█▂ beats 42/61	avg 63.423 points	▇ 1.4%	blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted	45.5000 points ✎	▁▁▅▁▄▁▄█▄▃▇▇ beats 54/61	avg 22.797 points	▇ 1.3%	blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted	86.2500 points ✎	▁·▁▁▁▁·▂▁▃▅█ beats 55/61	avg 66.987 points	▇ 1.2%	blunt
Decision Index Vision 0.4: private same skills (points)	68.7100 points ✎	▁▁▃▃▁▂▄▆▃▃▅█ beats 57/61	avg 48.067 points	▇ 1.2%	blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted	42.7900 points ✎	▆▃▃▆▄▄▇██▁▆▆ beats 43/61	avg 28.443 points	▇ 1.1%	blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted	76.1400 points ✎	▁·▂▂▁▃▃▅▅▃▂█ beats 60/61	avg 53.651 points	▇ 1.0%	blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted	79.9500 points ✎	▂▁▁▁▁▃▁▅▅▆██ beats 51/61	avg 62.137 points	▇ 0.9%	blunt

5 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted	97.2700 points ✎	▁·▁▂▁▁▃▁▂▂▅█ beats 48/61	avg 83.859 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted	33.7600 points ✎	▂▄▇▆█▄▄▇▂··▁ beats 47/61	avg 19.676 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted	79.3800 points ✎	▁···▁▂▂▂█▄▂▃ beats 61/61	avg 44.994 points	▇ 0.7%	blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted	77.3300 points ✎	▁▁▁▁▂▁▁▁▄█▃▃ beats 50/61	avg 67.662 points	▇ 0.6%	blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted	92.3900 points ✎	▁··▁▁▁▁▁▂▄█▁ beats 44/61	avg 85.184 points	▇ 0.4%	blunt

other tests2 not in a task · 7.7% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	62.3700 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 225/247	avg 41.206 points	▇▇ 4.9%	blunt
Decision Index 0.4.1: private new domains (equated points)	68.4800 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 209/247	avg 38.861 points	▇ 2.7%	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/mukaddamzaid ↗

$ how the score was worked out · Decision Index 0.4.1 68%, Etsabary · decision benchmarks 20%, Decision Index Vision 0.4 11%

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	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 68%	CC BY 4.0
Etsabary · decision benchmarks	2	▇▇▇▇▇▇ 20%	MIT
Decision Index Vision 0.4 · submitted; independent execution unverified	12	▇▇▇ 11%	CC BY 4.0
prior · pull toward the middle		▇ 1%
weighted average		= 68.7

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]	11.8%	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

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