whatmodel.sh / decision / simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e)

simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e)

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simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e) is an open-weights decision model from featherless-ai. Its published size is 35.951822704B parameters. Licence: apache-2.0.

Catalogue identity notes

DecisionBench v1 comparison: featherless-ai/simplejev-qwen3.6-35b-a3b, revision 995ad96eacd98c81ed38be0c5b274b04031597b0; language-model; adapter jev-compatible-server-v1; probability source option_letter_logit_softmax. Kept separate from newer or unpinned Decision Index recipes; standard prompt, not compact. No unverified runtime or OpenRouter price imported. 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 ↗

Published served parameter count; not a RAM or download-size measurement.

57.5±1.7#134 of 355 decision modelsfrom 27 benchmark results across 1 source

$ how it compares

The decision models ranked either side of simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e), out of 357 with a score, then more from featherless-ai.

#modelscorewhereRAMreleased
134Clef-flash Cloudflare58±1api $0.038/M input tokens +local~25GB2026-10
135Bespoke Nimble 9B v3 Bespoke Labs58±1local~21GB2026-10-06
136simplejev-qwen3.6-35b-a3b (DecisionBench 995ad96e) featherless-ai58±2model files
137Sieve 9B v2 Sthānika AI57±1model files2026-10-13
138Cerno 4B v1.1 apertixai57±1model files2026-10-19
more from featherless-ai
114simple-jev · Qwen3.8-27B (featherless) (decision readout) featherless-ai60±1source code
120simplejev-qwen3.8-27b (DecisionBench 1d4bf0f2) featherless-ai59±2model files

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

$ what it's good at

workflows▁▁▁▂▁▂▂▆█▄▁▁ #38 of 114 · 99% of its score · 27 tests

Beats vLLM-SR d3-flash (9B), Clef-omni, Jebadiah 27B v2.1 (Ollaya Q4_K_M) here, though they rank higher overall. Trails StartLux-Decision v1.1 2B, Solar Decide here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
DecisionBench v1 · action selection (all-request accuracy) submitted63.4% ✎▂▁▂▃▄▃▁▁▂█▇▄ beats 47/56medium · avg 51%▇▇▇▇▇▇▇▇ 21%at its level
DecisionBench v1 · routing (all-request accuracy) submitted77.0% ✎▁▁▁▁▂▂▁▁▁▁▃█ beats 51/56medium · avg 64%▇▇▇▇▇ 13%sharp · at its level
DecisionBench v1 · navigation (all-request accuracy) submitted74.0% ✎▁▁·▃▁▁▁▁▁▁▃█ beats 52/56medium · avg 58%▇▇▇▇ 11%sharp · at its level
DecisionBench v1 · record classification (all-request accuracy) submitted51.0% ✎▃▂▁▂▂▂▄▁▃▆██ beats 55/56medium · avg 39%▇▇▇▇ 10%at its level
DecisionBench v1 · verification (all-request accuracy) submitted61.5% ✎▁▁▅▁▃▂▂▁▁▇▇█ beats 42/56medium · avg 56%▇▇▇ 6.5%blunt · at its level
DecisionBench v1 · document record classification (all-request accuracy) submitted54.2% ✎▂▂·▁▂▄▃▆▄█▁▁ beats 42/56medium · avg 46%▇▇ 5.3%at its level
DecisionBench v1 · rubric scoring prioritization (all-request accuracy) submitted57.2% ✎▁▁▅▅▃▃▅█▃▃·▁ beats 50/56medium · avg 45%▇▇ 4.5%at its level
DecisionBench v1 · triage (all-request accuracy) submitted86.0% ✎▁·▁·▂▃▄▃▂█▄▂ beats 43/56easy · avg 78%▇▇ 4.1%sharp
19 more tests
testresultvs the others in its rundifficultycountswhy
DecisionBench v1 · completion assessment (all-request accuracy) submitted92.0% ✎▁▁▂▃▄·▂▁▁▆█▂ beats 39/56very easy · avg 86%▇ 3.7%sharp
DecisionBench v1 · content classification (all-request accuracy) submitted82.0% ✎▁····▁▁▁▁▁▁█ beats 56/56easy · avg 73%▇ 3.2%typical
DecisionBench v1 · bounded extraction (all-request accuracy) submitted95.0% ✎▃▃▂·▁▁▁▁▁▁█▅ beats 48/56very easy · avg 86%▇ 3.0%sharp · maxed out · noisy
DecisionBench v1 · review scoring (all-request accuracy) submitted62.0% ✎▁······▂▃▅▇█ beats 49/56medium · avg 52%▇ 2.9%at its level
DecisionBench v1 · retrieval ranking (all-request accuracy) submitted8.0% ✎▁▁·▁▁▃▃▂▃▁▁█ beats 8/56medium · avg 35%▇ 2.4%at its level · noisy
DecisionBench v1 · target selection (all-request accuracy) submitted5.0% ✎▁▁·▁▁▃▃▁▂▁▁█ beats 6/56hard · avg 29%▇ 2.3%at its level · noisy
DecisionBench v1 · risk scoring (all-request accuracy) submitted63.0% ✎▁▁·▁▂▂▁▃▃█▇▃ beats 29/56medium · avg 62%▇ 1.9%blunt · at its level
DecisionBench v1 · reasoning (all-request accuracy) submitted63.1% ✎▂·▁▁▆█▅▃▃▂▁▁ beats 44/56medium · avg 52%▇ 1.2%at its level
DecisionBench v1 · document workflows (all-request accuracy) submitted49.6% ✎█▄▃▁▁▃▂▂▁·▁▁ beats 14/56easy · avg 66%▇ 0.8%blunt · at its level
DecisionBench v1 · retrieval verification (all-request accuracy) submitted52.1% ✎█▁▂▁▁▁▁▁▂▅▁▁ beats 18/56easy · avg 74%▇ 0.7%noisy
DecisionBench v1 · guardrails moderation (all-request accuracy) submitted39.3% ✎▁▁▁▂▆▃▃█···▁ beats 21/56medium · avg 52%▇ 0.5%blunt · at its level · noisy
DecisionBench v1 · safety gating (all-request accuracy) submitted50.0% ✎▂·····▆█▂▂▄▇ beats 13/56easy · avg 77%▇ 0.4%noisy
DecisionBench v1 · document classification (all-request accuracy) submitted3.0% ✎▂▁·▂▃▁▁▄▁▂▂█ beats 10/56hard · avg 21%▇ 0.4%blunt · noisy
DecisionBench v1 · semantic filtering (all-request accuracy) submitted49.0% ✎▁·▁▁·▁▁█▂▃█▂ beats 6/56easy · avg 71%▇ 0.3%blunt · noisy
DecisionBench v1 · content moderation (all-request accuracy) submitted50.0% ✎▁····▃▅▃▂▂·█ beats 12/56easy · avg 82%▇ 0.2%noisy
DecisionBench v1 · context management (all-request accuracy) submitted50.0% ✎▁·····▁▇▆▁█▃ beats 7/56easy · avg 73%▇ 0.2%blunt · noisy
DecisionBench v1 · entity alignment (all-request accuracy) submitted19.7% ✎▁·▁▄▇▄▅▄▂▁▄█ beats 12/56easy · avg 66%▇ 0.2%at its level · noisy
DecisionBench v1 · function agent skill routing (all-request accuracy) submitted22.1% ✎▃▃▄▅▆▂▅▄▃▄█▃ beats 7/56easy · avg 68%▇ 0.1%blunt · at its level · noisy
DecisionBench v1 · routing triage (all-request accuracy) submitted0.0% ✎█▁···▁·▂▆▅▂▂ beats 7/56medium · avg 42%▇ 0.0%blunt · at its level · noisy

$ where to run it

Download model files ↗
Published model files verified. This is the revision recorded by the benchmark. 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/Qwen ↗

$ how the score was worked out · Hanno Labs DecisionBench v1 r… 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

sourceresultsshare of the scorelicence
Hanno Labs DecisionBench v1 reviewed results · submitted; independent execution unverified27CC0 1.0
prior · pull toward the middle
weighted average= 57.5

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