whatmodel.sh / decision / FLock this-that 1.2

FLock this-that 1.2

+ contribute

FLock this-that 1.2 is an open-weights decision model from FLock.io. Its published size is 1.88B parameters. Licence: mit.

Catalogue identity notes

Exact Decision Index tested engine this-that-1.2; reported model FLock this-that 1.2. Type: full fine-tune; technique: autoregressive. Implementation: https://github.com/FLock-io/this-that-model. 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.

39.7±1.1#263 of 355 decision modelsfrom 42 benchmark results across 1 source

$ how it compares

The decision models ranked either side of FLock this-that 1.2, out of 357 with a score.

#	model	score	where	RAM
263	Decision-1.0-Eos-0.8B (DecisionBench 3c2d6326) llm-semantic-router	41±1	local	~5.8GB
264	Decider 2B Mapika	41±1	model files
265	FLock this-that 1.2 FLock.io	40±1	model files
266	jdi-ptr14-0.8b AnamK	40±1	model files
267	Saina Helm 2.0 v2 Saina	39±1	model files

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

$ what it's good at

tools & automation▁▃▁▁▁▂▃▄▆██▆ #199 of 250 · 9.1% of its score · 6 tests

Beats Cam1, mini-jev Qwen3-4B (decision readout) 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	82.3% ✎	▁▂▁▁▁▃▂▄▅▆█▁ beats 50/246	very easy · avg 92%	▇▇ 4.3%	sharp · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted	52.4% ✎	▁▁▁▁▁▁▁▂▃▂█▂ beats 53/236	easy · avg 70%	▇ 2.4%	sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted	57.1% ✎	▁▁▁▂▃▅▅▆█▇█▃ beats 60/246	easy · avg 72%	▇ 1.1%	at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted	54.0% ✎	▁▁▁▁▁·▁▁▃▄█▁ beats 39/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted	0.0% ✎	█▁▁▃▄▄▆▄▁▂▁▃ beats 41/243	medium · avg 37%	▇ 0.5%	sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted	68.5% ✎	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▁▁▁·▁▁▁▃▃▃█▅ #206 of 258 · 5.1% of its score · 7 tests

Beats SemIf Qwen3.5-4B Base (decision readout), Metask-Jev-4B, Jobe Qwen3.5-4B (decision readout) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Mola-68M, Bosun v3.1 1.7B LoRA 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	19.5% ✎	▁▁▁▁▃▁▁▂▂▄▇█ beats 16/246	medium · avg 38%	▇ 1.6%	blunt · at its level
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted	37.8% ✎	▁▁▁▁▁▁▂▂▃▃█▅ beats 53/246	medium · avg 47%	▇ 1.6%	at its level
Decision Index 0.4.1: HoVer (accuracy) submitted	59.7% ✎	▆▆▇▅▄▄▃▇▄█▆▄ beats 48/246	easy · avg 74%	▇ 0.5%	blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted	66.1% ✎	▁▁▁▁▁▁▁▃▃▆█▄ beats 39/238	easy · avg 83%	▇ 0.5%	sharp · at its level · noisy
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted	50.0% ✎	█▅▅▄▃▂▁▁▁▁·▁ beats 20/245	easy · avg 70%	▇ 0.5%	at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted	71.6% ✎	▁·▁▁▁▁▁▁▂█▇█ beats 46/238	easy · avg 79%	▇ 0.3%	at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted	54.3% ✎	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▂▂▂▃▂▅▆▃█▆▄▃ #174 of 256 · 24% of its score · 9 tests

Beats Nari Decision 4B v3.2, Kev 4B r10, StartLux-Decision v1.1 0.8B here, though they rank higher overall. Trails DecisionTune 1.0, 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: HellaSwag (accuracy) submitted	80.7% ✎	▂▄▂▂▄▇▃▇█▅▃▁ beats 81/246	very easy · avg 85%	▇▇▇▇ 8.9%	sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted	67.6% ✎	▁▁▁▂▂▃▃▄▇▇█▄ beats 67/246	easy · avg 74%	▇▇ 5.3%	at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted	49.7% ✎	▁▂▃▅▅█▂····▁ beats 65/246	medium · avg 60%	▇▇ 4.4%	at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted	19.4% ✎	▁·▁·▁▁▂▄▅█▇▄ beats 22/246	medium · avg 44%	▇ 1.5%	at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted	64.7% ✎	▁▁▁▁▁▁▁▂▃▇▇█ beats 57/246	easy · avg 71%	▇ 1.0%	at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted	74.7% ✎	▁···▁▁▁▁▃▆█▃ beats 55/246	easy · avg 84%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted	50.0% ✎	▁▁▁▂▅▄▄▂▄▆█▄ beats 76/246	medium · avg 62%	▇ 0.8%	at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted	14.2% ✎	▁▁▁▁▁▃▁▁▁▃▆█ beats 18/246	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	7.3% ✎	▁··▂▃▃▅▇█▇▃▃ beats 38/246	hard · avg 22%	▇ 0.5%	noisy

arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #206 of 247 · 7.8% 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	43.6% ✎	▁▁▂▃▃▃▇▅█▅▃▁ beats 43/246	medium · avg 61%	▇ 3.4%	at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted	55.3% ✎	▁█▄▄▅█▆▅▄▁▁▁ beats 41/246	easy · avg 83%	▇ 1.6%	sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted	60.4% ✎	▁·▁▃▂▂▅█▄▂▁▁ beats 103/246	medium · avg 60%	▇ 1.5%	blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted	58.1% ✎	▁········▁▇█ beats 79/246	medium · avg 60%	▇ 0.8%	blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted	1.4% ✎	▄▅▅▃▆▅▃▅▂▅▃█ beats 22/237	hard · avg 21%	▇ 0.3%	sharp · noisy
Decision Index 0.4.1: Habermas Machine (accuracy) submitted	40.6% ✎	▁▂▄█▇▅▁▁▄▄▁▁ beats 76/246	medium · avg 47%	▇ 0.2%	blunt · at its level

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #185 of 263 · 47% of its score · 14 tests

Beats baselabs joey-1 (2B), Aurelis-2B, StartLux-Decision v1.1 0.8B here, though they rank higher overall.

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted	83.2% ✎	▂▂▂▂▂▂▃▃▄▆█▆ beats 73/246	very easy · avg 90%	▇▇▇▇ 8.8%	sharp
Decision Index 0.4.1: MMLU (accuracy) submitted	59.6% ✎	▁▄▄▃▃▃▅▇▅█▇▁ beats 73/246	easy · avg 70%	▇▇▇ 7.2%	sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted	92.1% ✎	▁▁▂▁▂▂▃▂▃▆█▅ beats 74/246	very easy · avg 96%	▇▇▇ 6.8%	sharp · noisy
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted	37.2% ✎	▄▄▃▃▂▄▅▇██▅▁ beats 76/246	medium · avg 46%	▇▇▇ 6.8%	sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted	48.7% ✎	▄▆▄▄█▇▇▄▃▁▁▁ beats 61/246	easy · avg 66%	▇▇ 5.9%	at its level
Decision Index 0.4.1: WinoGrande (accuracy) submitted	67.4% ✎	█▅█▅▄█▆▄▃▃▁▁ beats 68/246	easy · avg 78%	▇ 3.5%	at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted	22.7% ✎	▁··▄█▆▆▆▅▅▃▁ beats 48/246	medium · avg 45%	▇ 2.2%	sharp · at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted	33.2% ✎	▂▆▅▅▆█▆▃▁··▁ beats 76/246	medium · avg 39%	▇ 2.1%	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	54.6% ✎	▁▁▂█▅▄▁▁▁▁▁▁ beats 60/246	medium · avg 60%	▇ 1.0%	blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted	56.4% ✎	▁███▆▅▃▃▁▁▁▁ beats 51/246	easy · avg 71%	▇ 0.9%	at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted	31.9% ✎	██▄▃▃▄▁▁···▁ beats 9/246	medium · avg 58%	▇ 0.9%	at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted	31.3% ✎	▁▁▁▁▁▁▁▂▅█▂▁ beats 162/246	hard · avg 22%	▇ 0.7%	typical
Decision Index 0.4.1: ChessBench (accuracy) submitted	8.7% ✎	▄▇▄▄▄▆▄█▄▁▁▁ beats 40/246	hard · avg 16%	▇ 0.4%	blunt
Decision Index 0.4.1: HLE (accuracy) submitted	12.4% ✎	▁▁▂▃▆█▇▅▅▃▁▁ beats 124/246	very hard · avg 13%	▇ 0.0%	blunt

other tests2 not in a task · 6.2% of its score

test	result	vs the others in its run	difficulty	counts	why
Decision Index 0.4.1: private same skills (equated points)	26.7800 points ✎	▂▂▂▃▃▃▄▅▅▇█▃ beats 56/247	avg 41.206 points	▇▇ 4.0%	blunt
Decision Index 0.4.1: private new domains (equated points)	21.9700 points ✎	▃█▃▃▂▆▃▃▄▄▄▄ beats 78/247	avg 38.861 points	▇ 2.2%	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/flock-io ↗

$ 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		= 39.7

not counted (2)

Decision Index 0.4.1	Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]	68.5%	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]	54.3%	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