Lychee-27B

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Lychee-27B is an open-weights decision model from LycheeAI. Its published size is 26.09B parameters. Licence: cc-by-nc-4.0.

Catalogue identity notes

Exact Decision Index tested engine lychee-27b; reported model Lychee-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

· Weights licence ↗ · Parameter count ↗

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

66.3±1.4#44 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Lychee-27B, out of 357 with a score.

#	model	score	where	released
42	bosun-v3.1-1.7b (DecisionBench 2ef2d972) Hanno Labs	67±2	model files
43	Decider 31B (NVFP4) Mapika	66±1	model files	2026-10
44	Lychee-27B LycheeAI	66±1	model files
45	Darwin-27B-ZTC FINAL_Bench	66±1	model files
46	FlexDM · Gemma-4-31B (decision readout) 1000luca	66±1	source code

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$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #66 of 250 · 5.9% of its score · 6 tests

Beats mogan-decision-31B-it, Sieve 27B v2 here, though they rank higher overall. Trails baselabs joey-1 (2B), Solomon v1.1, Amber 4B 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	86.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 199/236	easy · avg 70%	▇ 1.7%	sharp · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	66.5% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 176/246	medium · avg 60%	▇ 1.1%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	80.7% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 194/243	medium · avg 37%	▇ 1.1%	sharp · noisy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted	96.9% ✎	▁▂▁▁▁▂▂▄▅▆█▁ beats 180/246	very easy · avg 92%	▇ 1.0%	sharp · maxed out · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	81.9% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 154/246	easy · avg 72%	▇ 1.0%	noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	79.8% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #72 of 258 · 7.7% of its score · 7 tests

Beats AutoTrust-JEV-27B v1.1, oenogarum (Gemma 4 31B), Decider 31B (NVFP4) here, though they rank higher overall. Trails StartLux-Decision v1.1 0.8B, Standard One 8B SH (v4), StartLux-Decision v1.1 2B 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	49.7% ✎	▁▁▁▁▁▁▁▂▂▄▇█ beats 228/246	medium · avg 38%	▇ 3.2%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	57.0% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 180/246	medium · avg 47%	▇ 2.8%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	82.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 165/246	easy · avg 74%	▇ 0.6%	blunt
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	76.4% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 159/245	easy · avg 70%	▇ 0.6%	noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	80.7% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 105/238	easy · avg 79%	▇ 0.3%	noisy
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	92.1% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 157/238	easy · avg 83%	▇ 0.3%	sharp · maxed out · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	40.9% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #65 of 256 · 22% of its score · 9 tests

Beats Turion Jev 31B, AJev lm6q (Gemma 4 31B), oenogarum (Gemma 4 31B) here, though they rank higher overall. Trails Decider 35B-A3B, Sieve 9B v2, Clef-flash 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	73.0% ✎	▁▂▃▅▅█▂····▁ beats 175/246	medium · avg 60%	▇▇ 5.5%	typical
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	86.5% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 233/246	easy · avg 74%	▇▇ 5.2%	typical
Decision Index 0.4.1: HellaSwag (accuracy) submitted	94.6% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 188/246	very easy · avg 85%	▇ 3.0%	sharp · maxed out
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	70.5% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 235/246	medium · avg 44%	▇ 2.8%	at its level
Decision Index 0.4.1: ACOS (per-review F1) submitted	26.6% ✎	▁··▂▃▃▅▇█▇▃▃ beats 151/246	hard · avg 22%	▇ 1.8%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	75.1% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 172/246	medium · avg 62%	▇ 1.1%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	76.2% ✎	▁▁▁▁▁▁▁▂▂▇▇█ beats 129/246	easy · avg 71%	▇ 1.0%	noisy
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	80.0% ✎	▁▁▁▁▁▁▁▁▁▃▆█ beats 172/246	easy · avg 66%	▇ 0.7%	noisy

1 more test

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: FinEntity (macro-F1) submitted	94.9% ✎	▁···▁▁▁▁▃▆█▃ beats 233/246	easy · avg 84%	▇ 0.5%	maxed out · noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #46 of 247 · 10% of its score · 6 tests

Beats Jeffan-31b-1710, vLLM-SR d3-turbo v1.1 (27B), Nace.AI Drex Max v1 (27B) here, though they rank higher overall. Trails Kas 4B, baselabs joey-1 (2B), Clef-flash 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	75.0% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 190/246	medium · avg 61%	▇▇ 4.0%	typical
Decision Index 0.4.1: Humicroedit (accuracy) submitted	61.0% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 117/246	medium · avg 60%	▇ 2.3%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	55.8% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 171/237	hard · avg 21%	▇ 1.3%	sharp · at its level · noisy
Decision Index 0.4.1: cfcolor (accuracy) submitted	66.1% ✎	▁········▁▇█ beats 207/246	medium · avg 60%	▇ 1.3%	blunt · at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	95.5% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 203/246	easy · avg 83%	▇ 0.9%	sharp · maxed out · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.0% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 64/246	medium · avg 47%	▇ 0.4%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #42 of 263 · 43% of its score · 14 tests

Beats vera-large, OneJev1.6-27B, baselabs elephant-1 (9B) 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
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	70.5% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 211/246	medium · avg 46%	▇▇▇▇▇ 11%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	83.5% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 209/246	easy · avg 66%	▇▇ 5.9%	typical
Decision Index 0.4.1: MMLU (accuracy) submitted	87.4% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 212/246	easy · avg 70%	▇▇ 5.9%	sharp
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	52.5% ✎	▂▆▅▅▆█▆▃▁··▁ beats 219/246	medium · avg 39%	▇▇ 4.1%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	75.0% ✎	▁··▄█▆▆▆▅▅▃▁ beats 203/246	medium · avg 45%	▇ 3.7%	sharp · at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	92.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 209/246	easy · avg 78%	▇ 2.7%	typical
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	32.6% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 180/246	hard · avg 22%	▇ 2.1%	at its level
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	96.7% ✎	▂▂▂▂▂▂▁▃▄▆█▆ beats 179/246	very easy · avg 90%	▇ 1.8%	sharp · maxed out

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	70.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 220/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	86.3% ✎	██▄▃▃▄▁▁···▁ beats 223/246	medium · avg 58%	▇ 1.2%	at its level · noisy
Decision Index 0.4.1: ChessBench (accuracy) submitted	17.4% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 141/246	hard · avg 16%	▇ 1.0%	blunt
Decision Index 0.4.1: CLadder (accuracy) submitted	80.6% ✎	▁███▆▅▃▃▁▁▁▁ beats 180/246	easy · avg 71%	▇ 1.0%	typical
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	99.2% ✎	▁▁▂▁▂▂▂▂▃▆█▅ beats 215/246	very easy · avg 96%	▇ 0.7%	sharp · maxed out · noisy
Decision Index 0.4.1: HLE (accuracy) submitted	17.2% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 232/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 11% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	62.1900 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 222/247	avg 41.206 points	▇▇▇ 6.8%	blunt
Decision Index 0.4.1: private new domains (equated points)	75.0900 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 239/247	avg 38.861 points	▇▇ 3.8%	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/LycheeAI ↗

$ 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		= 66.3

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	79.8%	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]	40.9%	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