whatmodel.sh / decision / rlcd-modernbert-151m (DecisionBench 8af2496e)

rlcd-modernbert-151m (DecisionBench 8af2496e)

+ contribute
Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

rlcd-modernbert-151m (DecisionBench 8af2496e) is an open-weights decision model from heman10x. Its published size is 0.151378176B parameters. Licence: apache-2.0.

Catalogue identity notes

DecisionBench v1 comparison: heman10x/rlcd-modernbert-151m, revision 8af2496eb63c7fa66d7d234e1f62629380030eb4; classifier; adapter jev-compatible-server-v1:gliclass_calibrated; probability source native_probability_distribution. 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.

26.2±1.6#325 of 355 decision modelsfrom 27 benchmark results across 1 source

$ how it compares

The decision models ranked either side of rlcd-modernbert-151m (DecisionBench 8af2496e), out of 357 with a score, then more from heman10x.

#modelscorewhereRAMreleased
325LFM2.5-2.6B-RLCD monotykamary26±1model files
326gliner2-large-v1 (DecisionBench f32ea6ef) Fastino26±2model files
327rlcd-modernbert-151m (DecisionBench 8af2496e) heman10x26±2model files
328JevK5 Lite alibiserikbay25±1model files
329Von 1.3 wfzyx25±1model files2026-09-28
more from heman10x
341Verdict heman10x21±1model files

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

$ what it's good at

workflows▁▁▁▃▁▂▂▆█▄▁▁ #101 of 114 · 99% of its score · 27 tests

Trails GLiNER2.5-Decide here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
DecisionBench v1 · action selection (all-request accuracy) submitted27.4% ✎▂▁▂▃▄▃▁▁▂█▇▄ beats 13/56medium · avg 51%▇▇▇▇▇▇ 15%at its level
DecisionBench v1 · routing (all-request accuracy) submitted24.3% ✎▁▁▁▁▃▂▁▁▁▁▃█ beats 8/56medium · avg 64%▇▇▇▇▇ 13%sharp · at its level
DecisionBench v1 · completion assessment (all-request accuracy) submitted54.0% ✎▁▁▂▃▄·▂▁▁▆█▂ beats 14/56very easy · avg 86%▇▇▇▇ 11%sharp · at its level
DecisionBench v1 · bounded extraction (all-request accuracy) submitted27.2% ✎▃▃▂·▁▁▁▁▁▁█▅ beats 12/56very easy · avg 86%▇▇▇▇ 10%sharp · at its level · noisy
DecisionBench v1 · navigation (all-request accuracy) submitted29.0% ✎▁▁·▃▁▁▃▁▁▁▃█ beats 18/56medium · avg 58%▇▇▇ 8.1%sharp
DecisionBench v1 · triage (all-request accuracy) submitted52.0% ✎▁·▁·▂▃▄▃▂█▄▂ beats 14/56easy · avg 78%▇▇▇ 7.2%sharp · at its level
DecisionBench v1 · verification (all-request accuracy) submitted34.5% ✎▁▁▅▁▃▂▂▁▁▇▇█ beats 4/56medium · avg 56%▇▇ 6.0%blunt · at its level
DecisionBench v1 · record classification (all-request accuracy) submitted23.0% ✎▃▂▁▂▃▂▄▁▃▆██ beats 12/56medium · avg 39%▇▇ 6.0%typical
19 more tests
testresultvs the others in its rundifficultycountswhy
DecisionBench v1 · content classification (all-request accuracy) submitted50.0% ✎▁····▁▁▁▁▃▁█ beats 13/56easy · avg 73%▇▇ 4.4%at its level
DecisionBench v1 · document record classification (all-request accuracy) submitted34.6% ✎▂▂·▁▂▄▃▆▄█▁▁ beats 17/56medium · avg 46%▇▇ 3.9%at its level
DecisionBench v1 · rubric scoring prioritization (all-request accuracy) submitted25.5% ✎▁▁▅▅▃▃▅█▃▃·▁ beats 6/56medium · avg 45%▇ 3.3%at its level
DecisionBench v1 · review scoring (all-request accuracy) submitted37.0% ✎▁······▂▃▅▇█ beats 13/56medium · avg 52%▇ 2.4%at its level
DecisionBench v1 · risk scoring (all-request accuracy) submitted47.0% ✎▁▁·▁▂▂▃▃▃█▇▃ beats 12/56medium · avg 62%▇ 2.0%blunt · at its level
DecisionBench v1 · reasoning (all-request accuracy) submitted40.3% ✎▂·▁▁▆█▅▃▃▂▁▁ beats 20/56medium · avg 52%▇ 1.0%at its level
DecisionBench v1 · retrieval verification (all-request accuracy) submitted48.5% ✎█▁▂▁▁▁▁▁▂▅▁▁ beats 2/56easy · avg 74%▇ 1.0%at its level · noisy
DecisionBench v1 · retrieval ranking (all-request accuracy) submitted0.0% ✎▃▁·▁▁▂▃▂▃▁▁█ beats 0/56medium · avg 35%▇ 0.9%noisy
DecisionBench v1 · target selection (all-request accuracy) submitted0.0% ✎▃▁·▁▁▁▃▁▂▁▁█ beats 0/56hard · avg 29%▇ 0.9%noisy
DecisionBench v1 · document workflows (all-request accuracy) submitted48.7% ✎█▄▃▁▁▃▂▂▁·▁▁ beats 7/56easy · avg 66%▇ 0.8%blunt · at its level
DecisionBench v1 · safety gating (all-request accuracy) submitted35.0% ✎▂·····▆█▂▂▄▇ beats 4/56easy · avg 77%▇ 0.7%at its level · noisy
DecisionBench v1 · guardrails moderation (all-request accuracy) submitted44.8% ✎▁▁▁▂▆▃▃█···▁ beats 25/56medium · avg 52%▇ 0.5%blunt · at its level · noisy
DecisionBench v1 · semantic filtering (all-request accuracy) submitted56.0% ✎▁·▁▁·▁▁█▂▃█▂ beats 19/56easy · avg 71%▇ 0.4%blunt · at its level · noisy
DecisionBench v1 · content moderation (all-request accuracy) submitted62.0% ✎▁····▃▅▃▂▂·█ beats 16/56easy · avg 82%▇ 0.3%at its level · noisy
DecisionBench v1 · context management (all-request accuracy) submitted64.0% ✎▁·····▁▇▆▁█▃ beats 22/56easy · avg 73%▇ 0.2%blunt · at its level · noisy
DecisionBench v1 · document classification (all-request accuracy) submitted0.0% ✎▃▁·▂▁▁▁▄▁▂▂█ beats 1/56hard · avg 21%▇ 0.2%blunt · noisy
DecisionBench v1 · entity alignment (all-request accuracy) submitted8.2% ✎▁·▁▄▇▄▅▄▂▁▄█ beats 4/56easy · avg 66%▇ 0.2%at its level · noisy
DecisionBench v1 · function agent skill routing (all-request accuracy) submitted5.6% ✎▃▃▄▅▆▂▅▄▃▄█▃ beats 1/56easy · avg 68%▇ 0.1%blunt · at its level · noisy
DecisionBench v1 · routing triage (all-request accuracy) submitted0.0% ✎█▁···▁·▂▆▅▂▂ beats 5/56medium · 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/heman10x ↗

$ 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= 26.2

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit 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 · sources and licences · json