whatmodel.sh / decision / Valen-0.8B

Valen-0.8B is an open-weights decision model from Valen. Its published size is 0.85B parameters. Licence: apache-2.0.

Catalogue identity notes

Exact Decision Index tested engine valen-0.8b-r2; reported model Valen-0.8B. 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.

33.6±1.0#286 of 355 decision modelsfrom 54 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of Valen-0.8B, out of 357 with a score, then more from Valen.

#modelscorewhereRAMreleased
286tasksource Decider nano v5 (150M) tasksource34±1model files
287JEV Ettin 150M Elfsong34±1model files2026-10-23
288Valen-0.8B Valen34±1model files
289JPT-0.8B Qwen3.5-0.8B LoRA kirp33±1model files
290CLM v0.1 (JevBench mini) Contrastive-LM33±2source code
more from Valen
227Valen-4B Valen48±1model files
268Valen-2B Valen39±1model files

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

$ what it's good at

tools & automation▁▃▁▁▃▂▃▄▆██▆ #217 of 250 · 8.8% of its score · 6 tests

Beats Cam1 here, though they rank higher overall. Trails Prumo (rule-based engine), JevK5 Lite, Crivo-32M v2 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: BFCL (case exact accuracy) submitted69.5% ✎▁▂▁▁▃▂▂▄▅▆█▁ beats 32/246very easy · avg 92%▇▇ 4.9%sharp · at its level · noisy
Decision Index 0.4.1: API-Bank (accuracy) submitted46.1% ✎▁▁▁▁▁▁▁▃▃▂█▂ beats 39/236easy · avg 70%▇ 2.0%sharp · at its level · noisy
Decision Index 0.4.1: When2Call (accuracy) submitted40.1% ✎▁▁▁▂▃▅▅▆█▇█▃ beats 27/246easy · avg 72%▇ 1.0%at its level · noisy
Decision Index 0.4.1: ToolRet (nDCG@10) submitted54.6% ✎▁▁▁▁▁·▁▁▃▄█▁ beats 41/246medium · avg 60%▇ 0.7%blunt · at its level
Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted0.0% ✎█▁▁▃▄▄▆▄▁▂▁▃ beats 5/243medium · avg 37%▇ 0.2%sharp · noisy
Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted77.0% ✎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▁▁▁·▁▁▃▁▃▃█▅ #232 of 258 · 4.4% of its score · 7 tests

Beats Sieve 2B, Strands Decider 2B (Hobson v21) here, though they rank higher overall. Trails Bosun v3.1 0.6B LoRA, Crivo-32M v2, Jev-Style 0.8B v3 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted27.6% ✎▁▁▁▁▁▁▃▂▃▃█▅ beats 28/246medium · avg 47%▇ 1.3%at its level
Decision Index 0.4.1: BRIGHT (nDCG@10) submitted28.5% ✎▁▁▁▁▁▁▁▃▂▄▇█ beats 42/246medium · avg 38%▇ 1.3%blunt · at its level
Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted17.8% ✎▁▁▁▁▁▃▁▂▃▆█▄ beats 16/238easy · avg 83%▇ 0.5%sharp · at its level · noisy
Decision Index 0.4.1: HoVer (accuracy) submitted54.7% ✎▆▆▇▅▄▄▃▇▄█▆▄ beats 22/246easy · avg 74%▇ 0.5%blunt · at its level
Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted51.1% ✎█▅▅▄▃▂▁▁▁▁·▁ beats 47/245easy · avg 70%▇ 0.4%at its level · noisy
Decision Index 0.4.1: BANKING77 (macro-F1) submitted60.0% ✎▁·▁▁▁▁▁▁▃█▇█ beats 23/238easy · avg 79%▇ 0.3%at its level · noisy
Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted57.9% ✎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▂▂▃▃▂▅▆▃█▆▄▃ #229 of 256 · 22% of its score · 9 tests

Trails JevK5 Lite, LFM2.5-2.6B-RLCD, JEV Ettin 400M here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: HellaSwag (accuracy) submitted43.9% ✎▂▄▂▂▄▇▃▇█▅▃▁ beats 26/246very easy · avg 85%▇▇▇▇ 8.8%sharp · at its level
Decision Index 0.4.1: NLI4CT (macro-F1) submitted64.6% ✎▁▁▁▂▂▃▃▄▇▇█▄ beats 58/246easy · avg 74%▇▇ 4.8%at its level
Decision Index 0.4.1: ANLI (macro-F1) submitted40.2% ✎▁▂▃▅▅█▂····▁ beats 36/246medium · avg 60%▇ 3.7%at its level
Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted14.7% ✎▁·▁·▁▁▃▄▅█▇▄ beats 11/246medium · avg 44%▇ 1.2%at its level
Decision Index 0.4.1: ContractNLI (macro-F1) submitted78.3% ✎▁▁▁▁▁▁▁▂▂▇▇█ beats 146/246easy · avg 71%▇ 0.9%at its level · noisy
Decision Index 0.4.1: FinEntity (macro-F1) submitted74.9% ✎▁···▁▁▁▁▃▆█▃ beats 58/246easy · avg 84%▇ 0.8%at its level · noisy
Decision Index 0.4.1: VAST (macro-F1) submitted43.4% ✎▁▁▁▂▅▄▄▂▄▆█▄ beats 47/246medium · avg 62%▇ 0.7%at its level
Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted53.1% ✎▁▁▁▁▁▁▁▁▁▃▆█ beats 60/246easy · avg 66%▇ 0.6%at its level · noisy
1 more test
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ACOS (per-review F1) submitted12.3% ✎▁··▂▃▃▅▇█▇▃▃ beats 70/246hard · avg 22%▇ 0.4%noisy
arts & human taste▁▇▄▃▅▅█▅▄▂▁▁ #223 of 247 · 6.7% of its score · 6 tests

Beats Valen-4B, TokenRhythm NeoHorse-Jev-4B, jiwo 0.8B v2 here, though they rank higher overall. Trails LFM2.5-350M-RLCD, system-one-gemma, Bekko System One v0 17M here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: New Yorker (accuracy) submitted37.7% ✎▁▁▂▃▃▃▇▅█▅▃▁ beats 31/246medium · avg 61%▇ 2.8%at its level
Decision Index 0.4.1: BPoMP (accuracy) submitted50.6% ✎▁█▄▄▅█▆▅▄▁▁▁ beats 24/246easy · avg 83%▇ 1.6%sharp · at its level · noisy
Decision Index 0.4.1: Humicroedit (accuracy) submitted55.1% ✎▁·▁▃▂▃▅█▄▂▁▁ beats 58/246medium · avg 60%▇ 1.3%blunt · at its level
Decision Index 0.4.1: cfcolor (accuracy) submitted58.6% ✎▁········▁▇█ beats 88/246medium · avg 60%▇ 0.7%blunt · at its level
Decision Index 0.4.1: Habermas Machine (accuracy) submitted44.9% ✎▁▂▄█▇▅▁▁▄▄▁▁ beats 133/246medium · avg 47%▇ 0.2%blunt · at its level
Decision Index 0.4.1: POP909-CL (accuracy) submitted0.9% ✎▄▅▅▃▆▅▃▅▂▅▃█ beats 15/237hard · avg 21%▇ 0.1%sharp · too hard for it · noisy
knowledge & reasoning▁▂▂▂▃▃▃▅▅▆█▂ #209 of 263 · 44% 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 here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: ARC-Challenge (accuracy) submitted70.5% ✎▂▂▂▂▃▂▁▃▄▆█▆ beats 54/246very easy · avg 90%▇▇▇▇ 9.4%sharp · at its level
Decision Index 0.4.1: ARC-Easy (accuracy) submitted85.3% ✎▁▁▂▁▂▃▂▂▃▆█▅ beats 51/246very easy · avg 96%▇▇▇▇ 9.2%sharp · noisy
Decision Index 0.4.1: MMLU (accuracy) submitted50.2% ✎▁▄▄▃▃▂▅▇▅█▇▁ beats 56/246easy · avg 70%▇▇ 6.2%sharp · at its level
Decision Index 0.4.1: BBH (accuracy) submitted46.1% ✎▄▆▄▄█▇▇▄▃▁▁▁ beats 54/246easy · avg 66%▇▇ 5.0%at its level
Decision Index 0.4.1: MMLU-Pro (accuracy) submitted28.9% ✎▄▄▃▃▂▄▅▇██▅▁ beats 60/246medium · avg 46%▇▇ 4.9%sharp
Decision Index 0.4.1: WinoGrande (accuracy) submitted55.9% ✎█▅█▅▄█▆▄▃▃▁▁ beats 33/246easy · avg 78%▇ 3.2%at its level
Decision Index 0.4.1: GPQA Diamond (accuracy) submitted26.0% ✎▂▆▅▅▆█▆▃▁··▁ beats 24/246medium · avg 39%▇ 1.7%blunt · at its level
Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted26.8% ✎▁··▄█▆▆▆▅▅▃▁ beats 65/246medium · avg 45%▇ 1.6%sharp
6 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: MuSR (accuracy) submitted53.2% ✎▁▁▃█▅▄▁▁▁▁▁▁ beats 46/246medium · avg 60%▇ 0.8%blunt · at its level
Decision Index 0.4.1: CLadder (accuracy) submitted54.8% ✎▁███▆▅▃▃▁▁▁▁ beats 41/246easy · avg 71%▇ 0.8%at its level
Decision Index 0.4.1: CRUXEval (accuracy) submitted31.2% ✎██▄▃▃▄▁▁···▁ beats 7/246medium · avg 58%▇ 0.7%at its level · noisy
Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted10.2% ✎▁▁▁▁▁▁▃▂▅█▂▁ beats 44/246hard · avg 22%▇ 0.5%typical
Decision Index 0.4.1: ChessBench (accuracy) submitted7.4% ✎▄▇▄▄▄▆▄█▄▁▁▁ beats 9/246hard · avg 16%▇ 0.3%blunt
Decision Index 0.4.1: HLE (accuracy) submitted12.4% ✎▁▁▂▃▆█▇▅▅▃▁▁ beats 120/246very hard · avg 13%▇ 0.0%blunt
vision▁·▃▂▃▃▇▄▄█▄▃ #74 of 79 · 7.9% of its score · 12 tests

Beats vLLM-SR d3-lite (0.8B), Saina Helm 2 Omni (0.8B) here, though they rank higher overall. Trails LiquidAI d1-omni-600M here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted40.6600 points ✎▁·▁▃▃▁▄▄▃▅█▂ beats 3/61avg 63.423 points▇ 1.0%blunt
Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted7.7800 points ✎▁▁▅▁▄▁▄█▄▃▇▇ beats 5/61avg 22.797 points▇ 0.9%blunt
Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted42.2500 points ✎▁·▃▁▁▁·▂▁▃▅█ beats 2/61avg 66.987 points▇ 0.8%blunt
Decision Index Vision 0.4: private same skills (points)39.6700 points ✎▁▁▃▃▁▂▄▆▃▃▅█ beats 9/61avg 48.067 points▇ 0.8%blunt
Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted11.7900 points ✎▆▃▃▆▄▄▇██▁▆▆ beats 2/61avg 28.443 points▇ 0.7%blunt
Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted47.2800 points ✎▁·▂▂▁▃▃▅▅▃▂█ beats 9/61avg 53.651 points▇ 0.7%blunt
Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted57.6400 points ✎▂▁▁▁▁▃▁▅▅▆██ beats 12/61avg 62.137 points▇ 0.6%blunt
Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted79.7800 points ✎▁·▁▂▁▃▃▁▂▂▅█ beats 12/61avg 83.859 points▇ 0.5%blunt
4 more tests
testresultvs the others in its rundifficultycountswhy
Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted16.4400 points ✎▂▄▇▆█▄▄▇▂··▁ beats 13/61avg 19.676 points▇ 0.5%blunt
Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted35.8800 points ✎▁···▁▃▂▂█▄▂▃ beats 9/61avg 44.994 points▇ 0.5%blunt
Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted62.5200 points ✎▁▁▁▁▃▁▁▁▄█▃▃ beats 7/61avg 67.662 points▇ 0.4%blunt
Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted77.0900 points ✎▁··▁▁▃▁▁▂▄█▁ beats 5/61avg 85.184 points▇ 0.3%blunt
other tests2 not in a task · 5.3% of its score
testresultvs the others in its rundifficultycountswhy
Decision Index 0.4.1: private same skills (equated points)18.7700 points ✎▂▂▂▃▃▃▄▅▅▇█▃ beats 33/247avg 41.206 points▇ 3.4%blunt
Decision Index 0.4.1: private new domains (equated points)13.2300 points ✎▃█▃▃▂▆▃▃▄▄▄▄ beats 43/247avg 38.861 points▇ 1.9%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/Valen-Team ↗

$ how the score was worked out · Decision Index 0.4.1 92%, Decision Index Vision 0.4 8%

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

sourceresultsshare of the scorelicence
Decision Index 0.4.1 · submitted; independent execution unverified42CC BY 4.0
Decision Index Vision 0.4 · submitted; independent execution unverified12CC BY 4.0
prior · pull toward the middle
weighted average= 33.6

not counted (2)

Decision Index 0.4.1Decision Index 0.4.1: RouterBench (selected quality (quality objective)) [correct]77.0%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 0.4.1Decision Index 0.4.1: SGD/SGD-X (macro-F1) [correct]57.9%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

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 · sources and licences · json