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Valen-0.8B
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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.
$ how it compares
The decision models ranked either side of Valen-0.8B, out of 357 with a score, then more from Valen.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 286 | 34±1 | model files | |||
| 287 | JEV Ettin 150M | 34±1 | model files | ||
| 288 | 34±1 | model files | |||
| 289 | 33±1 | model files | |||
| 290 | 33±2 | source code | |||
| more from Valen | |||||
| 227 | 48±1 | model files | |||
| 268 | 39±1 | model 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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: BFCL (case exact accuracy) submitted | 69.5% ✎ | ▁▂▁▁▃▂▂▄▅▆█▁ beats 32/246 | 4.9% |
| Decision Index 0.4.1: API-Bank (accuracy) submitted | 46.1% ✎ | ▁▁▁▁▁▁▁▃▃▂█▂ beats 39/236 | 2.0% |
| Decision Index 0.4.1: When2Call (accuracy) submitted | 40.1% ✎ | ▁▁▁▂▃▅▅▆█▇█▃ beats 27/246 | 1.0% |
| Decision Index 0.4.1: ToolRet (nDCG@10) submitted | 54.6% ✎ | ▁▁▁▁▁·▁▁▃▄█▁ beats 41/246 | 0.7% |
| Decision Index 0.4.1: Home appliance simulator (case exact accuracy) submitted | 0.0% ✎ | █▁▁▃▄▄▆▄▁▂▁▃ beats 5/243 | 0.2% |
| Decision Index 0.4.1: RouterBench (selected quality (quality objective)) submitted | 77.0% ✎ | no other model yet | — |
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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: Amazon ESCI (macro-F1) submitted | 27.6% ✎ | ▁▁▁▁▁▁▃▂▃▃█▅ beats 28/246 | 1.3% |
| Decision Index 0.4.1: BRIGHT (nDCG@10) submitted | 28.5% ✎ | ▁▁▁▁▁▁▁▃▂▄▇█ beats 42/246 | 1.3% |
| Decision Index 0.4.1: CLINC150+OOS (macro-F1) submitted | 17.8% ✎ | ▁▁▁▁▁▃▁▂▃▆█▄ beats 16/238 | 0.5% |
| Decision Index 0.4.1: HoVer (accuracy) submitted | 54.7% ✎ | ▆▆▇▅▄▄▃▇▄█▆▄ beats 22/246 | 0.5% |
| Decision Index 0.4.1: PhishNChips phishing decisions (accuracy) submitted | 51.1% ✎ | █▅▅▄▃▂▁▁▁▁·▁ beats 47/245 | 0.4% |
| Decision Index 0.4.1: BANKING77 (macro-F1) submitted | 60.0% ✎ | ▁·▁▁▁▁▁▁▃█▇█ beats 23/238 | 0.3% |
| Decision Index 0.4.1: SGD/SGD-X (macro-F1) submitted | 57.9% ✎ | no other model yet | — |
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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: HellaSwag (accuracy) submitted | 43.9% ✎ | ▂▄▂▂▄▇▃▇█▅▃▁ beats 26/246 | 8.8% |
| Decision Index 0.4.1: NLI4CT (macro-F1) submitted | 64.6% ✎ | ▁▁▁▂▂▃▃▄▇▇█▄ beats 58/246 | 4.8% |
| Decision Index 0.4.1: ANLI (macro-F1) submitted | 40.2% ✎ | ▁▂▃▅▅█▂····▁ beats 36/246 | 3.7% |
| Decision Index 0.4.1: iSarcasmEval (Sarcasm F1 · track A, English) submitted | 14.7% ✎ | ▁·▁·▁▁▃▄▅█▇▄ beats 11/246 | 1.2% |
| Decision Index 0.4.1: ContractNLI (macro-F1) submitted | 78.3% ✎ | ▁▁▁▁▁▁▁▂▂▇▇█ beats 146/246 | 0.9% |
| Decision Index 0.4.1: FinEntity (macro-F1) submitted | 74.9% ✎ | ▁···▁▁▁▁▃▆█▃ beats 58/246 | 0.8% |
| Decision Index 0.4.1: VAST (macro-F1) submitted | 43.4% ✎ | ▁▁▁▂▅▄▄▂▄▆█▄ beats 47/246 | 0.7% |
| Decision Index 0.4.1: RAGTruth (F1 on hallucinated class) submitted | 53.1% ✎ | ▁▁▁▁▁▁▁▁▁▃▆█ beats 60/246 | 0.6% |
1 more test
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: ACOS (per-review F1) submitted | 12.3% ✎ | ▁··▂▃▃▅▇█▇▃▃ beats 70/246 | 0.4% |
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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: New Yorker (accuracy) submitted | 37.7% ✎ | ▁▁▂▃▃▃▇▅█▅▃▁ beats 31/246 | 2.8% |
| Decision Index 0.4.1: BPoMP (accuracy) submitted | 50.6% ✎ | ▁█▄▄▅█▆▅▄▁▁▁ beats 24/246 | 1.6% |
| Decision Index 0.4.1: Humicroedit (accuracy) submitted | 55.1% ✎ | ▁·▁▃▂▃▅█▄▂▁▁ beats 58/246 | 1.3% |
| Decision Index 0.4.1: cfcolor (accuracy) submitted | 58.6% ✎ | ▁········▁▇█ beats 88/246 | 0.7% |
| Decision Index 0.4.1: Habermas Machine (accuracy) submitted | 44.9% ✎ | ▁▂▄█▇▅▁▁▄▄▁▁ beats 133/246 | 0.2% |
| Decision Index 0.4.1: POP909-CL (accuracy) submitted | 0.9% ✎ | ▄▅▅▃▆▅▃▅▂▅▃█ beats 15/237 | 0.1% |
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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: ARC-Challenge (accuracy) submitted | 70.5% ✎ | ▂▂▂▂▃▂▁▃▄▆█▆ beats 54/246 | 9.4% |
| Decision Index 0.4.1: ARC-Easy (accuracy) submitted | 85.3% ✎ | ▁▁▂▁▂▃▂▂▃▆█▅ beats 51/246 | 9.2% |
| Decision Index 0.4.1: MMLU (accuracy) submitted | 50.2% ✎ | ▁▄▄▃▃▂▅▇▅█▇▁ beats 56/246 | 6.2% |
| Decision Index 0.4.1: BBH (accuracy) submitted | 46.1% ✎ | ▄▆▄▄█▇▇▄▃▁▁▁ beats 54/246 | 5.0% |
| Decision Index 0.4.1: MMLU-Pro (accuracy) submitted | 28.9% ✎ | ▄▄▃▃▂▄▅▇██▅▁ beats 60/246 | 4.9% |
| Decision Index 0.4.1: WinoGrande (accuracy) submitted | 55.9% ✎ | █▅█▅▄█▆▄▃▃▁▁ beats 33/246 | 3.2% |
| Decision Index 0.4.1: GPQA Diamond (accuracy) submitted | 26.0% ✎ | ▂▆▅▅▆█▆▃▁··▁ beats 24/246 | 1.7% |
| Decision Index 0.4.1: GSM8K (accuracy (4- and 10-choice)) submitted | 26.8% ✎ | ▁··▄█▆▆▆▅▅▃▁ beats 65/246 | 1.6% |
6 more tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: MuSR (accuracy) submitted | 53.2% ✎ | ▁▁▃█▅▄▁▁▁▁▁▁ beats 46/246 | 0.8% |
| Decision Index 0.4.1: CLadder (accuracy) submitted | 54.8% ✎ | ▁███▆▅▃▃▁▁▁▁ beats 41/246 | 0.8% |
| Decision Index 0.4.1: CRUXEval (accuracy) submitted | 31.2% ✎ | ██▄▃▃▄▁▁···▁ beats 7/246 | 0.7% |
| Decision Index 0.4.1: SATA-Bench (case exact accuracy) submitted | 10.2% ✎ | ▁▁▁▁▁▁▃▂▅█▂▁ beats 44/246 | 0.5% |
| Decision Index 0.4.1: ChessBench (accuracy) submitted | 7.4% ✎ | ▄▇▄▄▄▆▄█▄▁▁▁ beats 9/246 | 0.3% |
| Decision Index 0.4.1: HLE (accuracy) submitted | 12.4% ✎ | ▁▁▂▃▆█▇▅▅▃▁▁ beats 120/246 | 0.0% |
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.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index Vision 0.4 · Mind2Web (chance-corrected points) submitted | 40.6600 points ✎ | ▁·▁▃▃▁▄▄▃▅█▂ beats 3/61 | 1.0% |
| Decision Index Vision 0.4 · MMMU-Pro vision (chance-corrected points) submitted | 7.7800 points ✎ | ▁▁▅▁▄▁▄█▄▃▇▇ beats 5/61 | 0.9% |
| Decision Index Vision 0.4 · Winoground (chance-corrected points) submitted | 42.2500 points ✎ | ▁·▃▁▁▁·▂▁▃▅█ beats 2/61 | 0.8% |
| Decision Index Vision 0.4: private same skills (points) | 39.6700 points ✎ | ▁▁▃▃▁▂▄▆▃▃▅█ beats 9/61 | 0.8% |
| Decision Index Vision 0.4 · Moderation (Hateful Memes) (chance-corrected points) submitted | 11.7900 points ✎ | ▆▃▃▆▄▄▇██▁▆▆ beats 2/61 | 0.7% |
| Decision Index Vision 0.4 · RealWorldQA (chance-corrected points) submitted | 47.2800 points ✎ | ▁·▂▂▁▃▃▅▅▃▂█ beats 9/61 | 0.7% |
| Decision Index Vision 0.4 · CharXiv (chance-corrected points) submitted | 57.6400 points ✎ | ▂▁▁▁▁▃▁▅▅▆██ beats 12/61 | 0.6% |
| Decision Index Vision 0.4 · InfographicVQA (chance-corrected points) submitted | 79.7800 points ✎ | ▁·▁▂▁▃▃▁▂▂▅█ beats 12/61 | 0.5% |
4 more tests
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index Vision 0.4 · R-Bench-M (chance-corrected points) submitted | 16.4400 points ✎ | ▂▄▇▆█▄▄▇▂··▁ beats 13/61 | 0.5% |
| Decision Index Vision 0.4 · BLINK (chance-corrected points) submitted | 35.8800 points ✎ | ▁···▁▃▂▂█▄▂▃ beats 9/61 | 0.5% |
| Decision Index Vision 0.4 · CV-Bench (chance-corrected points) submitted | 62.5200 points ✎ | ▁▁▁▁▃▁▁▁▄█▃▃ beats 7/61 | 0.4% |
| Decision Index Vision 0.4 · KIE (CORD+FUNSD) (chance-corrected points) submitted | 77.0900 points ✎ | ▁··▁▁▃▁▁▂▄█▁ beats 5/61 | 0.3% |
other tests2 not in a task · 5.3% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Decision Index 0.4.1: private same skills (equated points) | 18.7700 points ✎ | ▂▂▂▃▃▃▄▅▅▇█▃ beats 33/247 | 3.4% |
| Decision Index 0.4.1: private new domains (equated points) | 13.2300 points ✎ | ▃█▃▃▂▆▃▃▄▄▄▄ beats 43/247 | 1.9% |
$ 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
| source | results | share of the score |
|---|---|---|
| 42 | 92% | |
| 12 | 8% | |
| prior · pull toward the middle | 0% | |
| weighted average | = 33.6 |
not counted (2)
| Decision Index 0.4.1 | Decision 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 0.4.1 | Decision 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 |
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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.
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