wyat-1-800m

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wyat-1-800m is an open-weights decision model from teilomillet, released 18 October 2026. Its published size is 0.87B parameters. Licence: other.

Catalogue identity notes

Exact Decision Index tested engine wyat-1-800m; reported model wyat-1-800m. Type: LoRA; 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.

34.2±1.1#283 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of wyat-1-800m, out of 357 with a score.

#	model	score	where	RAM	released
283	Strands Decider 2B (Hobson v21) Amazon Web Services	36±1	local	~6.6GB	2026-10
284	vLLM-SR vela3-fast-vision (Vela 3.0, 0.25B) vLLM Semantic Router	35±1	model files
285	wyat-1-800m teilomillet	34±1	model files		2026-10-18
286	tasksource Decider nano v5 (150M) tasksource	34±1	model files
287	JEV Ettin 150M Elfsong	34±1	model files		2026-10-23

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

$ what it's good at

tools & automation▁▃▁▁▁▃▃▄▆██▆ #205 of 250 · 10% of its score · 6 tests

Beats Cam1, mini-jev Qwen3-4B (decision readout), InternLM Intern-Decision Qwen3.5-2B here, though they rank higher overall. Trails JevK5 Lite, Mola-68M, Crivo-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	78.3% ✎	▁▂▁▁▁▃▂▄▅▆█▁ beats 44/246	very easy · avg 92%	▇▇ 5.3%	sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	52.0% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 52/236	easy · avg 70%	▇ 2.2%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	46.0% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 34/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	58.3% ✎	▁▁▁▁▁·▁▁▁▄█▁ beats 57/246	medium · avg 60%	▇ 0.7%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 13/243	medium · avg 37%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	65.4% ✎	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▁▁▁·▁▁▁▁▃▃█▅ #186 of 258 · 4.8% of its score · 7 tests

Beats JevK5 9B v0.3.3, JevK5 v0.3, Hopper (G) 1.2 Qwen3.5-4B LoRA here, though they rank higher overall. Trails Mola-68M, Bosun v3.1 1.7B LoRA, Dinah-1 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	42.7% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 73/246	medium · avg 47%	▇ 1.4%	at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted	30.1% ✎	▁▁▁▁▁▁▁▃▂▄▇█ beats 51/246	medium · avg 38%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	85.9% ✎	▁▁▁▁▁▁▁▂▃▆█▄ beats 84/238	easy · avg 83%	▇ 0.6%	sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted	58.1% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 40/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	57.5% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 77/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	80.5% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 102/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	18.4% ✎	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▂▂▃▃▂▅▆▃█▆▄▃ #223 of 256 · 24% of its score · 9 tests

Trails JEV Ettin 400M, LiquidAI d1-omni-600M, Dinah-1 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	49.7% ✎	▂▄▃▂▄▇▃▇█▅▃▁ beats 33/246	very easy · avg 85%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	62.4% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 50/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	41.4% ✎	▁▂▃▅▅█▂····▁ beats 42/246	medium · avg 60%	▇▇ 4.0%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	28.8% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 56/246	medium · avg 44%	▇ 1.3%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	47.5% ✎	▁▁▁▁▁▁▃▂▂▇▇█ beats 32/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	70.0% ✎	▁···▁▁▁▁▃▆█▃ beats 41/246	easy · avg 84%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	45.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 60/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	14.1% ✎	▁▁▁▁▁▃▁▁▁▃▆█ beats 17/246	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	8.1% ✎	▁··▂▃▃▅▇█▇▃▃ beats 43/246	hard · avg 22%	▇ 0.4%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #203 of 247 · 7.4% of its score · 6 tests

Beats Valen-4B, Saracura PT-BR 4B, TokenRhythm NeoHorse-Jev-4B here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Qwen-2.5-1B-RLCD (decision readout) 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	41.3% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 38/246	medium · avg 61%	▇ 3.1%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	56.3% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 44/246	easy · avg 83%	▇ 1.7%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	55.6% ✎	▁·▁▃▂▃▅█▄▂▁▁ beats 63/246	medium · avg 60%	▇ 1.4%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	57.0% ✎	▁········▁▇█ beats 69/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	42.2% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 96/246	medium · avg 47%	▇ 0.2%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.5% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 30/237	hard · avg 21%	▇ 0.2%	sharp · too hard for it · noisy

knowledge & reasoning▁▂▂▂▃▃▃▅▅▆█▂ #213 of 263 · 48% of its score · 14 tests

Beats Crivo-1B, vLLM-SR vela3-fast (Vela 3.0, 0.4B), Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326) here, though they rank higher overall. Trails laya (DecisionBench 1c5edc17), DM-JEPA 1.1, Sifr 0.8B v3.1 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	67.8% ✎	▂▂▂▂▃▂▁▃▄▆█▆ beats 48/246	very easy · avg 90%	▇▇▇▇ 10%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	83.1% ✎	▁▁▂▁▂▃▂▂▃▆█▅ beats 49/246	very easy · avg 96%	▇▇▇▇ 10%	sharp · noisy
Decision Index 0.4.1: MMLU (accuracy) submitted	47.0% ✎	▁▄▄▃▃▂▅▇▅█▇▁ beats 49/246	easy · avg 70%	▇▇▇ 6.8%	sharp · at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	25.4% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 54/246	medium · avg 46%	▇▇ 5.5%	sharp
Decision Index 0.4.1: BBH (accuracy) submitted	43.6% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 48/246	easy · avg 66%	▇▇ 5.5%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	59.0% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 40/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	30.1% ✎	▂▆▅▅▆█▆▃▁··▁ beats 58/246	medium · avg 39%	▇ 1.9%	blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	29.4% ✎	▁··▄█▆▆▆▅▅▃▁ beats 78/246	medium · avg 45%	▇ 1.7%	sharp

6 more tests

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: MuSR (accuracy) submitted	50.9% ✎	▁▁▃█▅▄▁▁▁▁▁▁ beats 36/246	medium · avg 60%	▇ 0.9%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	55.1% ✎	▁███▆▅▃▃▁▁▁▁ beats 43/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	34.6% ✎	██▄▃▃▄▁▁···▁ beats 24/246	medium · avg 58%	▇ 0.8%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	18.1% ✎	▁▁▁▁▁▁▁▃▅█▂▁ beats 66/246	hard · avg 22%	▇ 0.5%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	8.6% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 38/246	hard · avg 16%	▇ 0.3%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	11.8% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 99/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 5.8% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	24.4500 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 50/247	avg 41.206 points	▇ 3.7%	blunt
Decision Index 0.4.1: private new domains (equated points)	17.0700 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 65/247	avg 38.861 points	▇ 2.1%	blunt

$ where to run it

Download model files ↗
Published model files verified. Includes adapters or readout weights; follow the model documentation for the required base model. 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/teilomillet ↗

$ 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		= 34.2

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	65.4%	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]	18.4%	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