whatmodel.sh / decision / Span-01 Pro

Span-01 Pro

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Span-01 Pro is a closed-weights decision model from Respan, released 24 September 2026. Licence: proprietary.

Catalogue identity notes

Named hosted endpoint verified 2026-10-31. Perch records the requested model and test date; the service may change its weights. No immutable current-weight equivalence asserted. Not merged with similarly named open-weight community checkpoints.

Model information sources

Release date ↗

50.1±9.1#205 of 355 decision modelsfrom 6 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Span-01 Pro, out of 357 with a score, then more from Respan.

#modelscorewhereRAMreleased
205Bespoke Nimble 9B v2 Bespoke Labs50±1local~20GB
206JevK5 v0.3 alibiserikbay50±1model files
207Span-01 Pro Respan50±9api price unknown2026-09-24
208Sieve 9B Sthānika AI50±1model files2026-10-13
209Kev 9B v2 Jared Palmer50±1model files2026-09-30
more from Respan
50Span-02 (Gemma 4 26B-A4B) Respan66±1api price unknown

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

$ what it's good at

workflows▁▁▁▂▁▂▂▆█▄▁▁ #70 of 114 · 65% of its score · 6 tests

Beats Clef-omni, baselabs joey-1 (2B), ZTC-Judge-9B (DecisionBench 05d154a5) here, though they rank higher overall. Trails Solar Decide Flash, InternLM Intern-Decision Qwen3.5-4B, StartLux-Decision v1.1 0.8B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Perch semantic lint · private (Youden J)0.3662 J ✎█····▄█▄···█ beats 2/7avg 0.380 J▇▇▇▇▇▇▇▇▇▇ 25%blunt
Perch semantic lint · public (Youden J)0.3879 J ✎█····▄█▄···█ beats 3/7avg 0.363 J▇▇▇▇▇▇▇▇▇ 23%blunt
Perch security detection · public (Youden J)0.0385 J ✎█···▄▄···▄▄█ beats 2/7avg 0.052 J▇▇ 5.1%blunt
Perch bug detection · private (Youden J)0.0424 J ✎▅··▃▃█·····▃ beats 3/7avg 0.027 J▇▇ 4.0%blunt
Perch bug detection · public (Youden J)0.0270 J ✎█▄·█·▄▄····▄ beats 3/7avg 0.026 J▇ 3.6%blunt
Perch security detection · private (Youden J)-0.0008 J ✎█▃▃··▃·▃···▃ beats 0/7avg 0.017 J▇ 3.6%blunt

$ where to run it

Through an API

api · price unknown · www.respan.ai ↗

Model repository and documentation: respan.ai ↗

$ how the score was worked out · Perch benchmark results 65%

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
Perch benchmark results6CC BY 4.0
prior · pull toward the middle
weighted average= 50.1

$ 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