French medical decision models by Bofeng Huang: pass a patient message or clinical note, a question and candidate answers, and get one probability per answer from a single forward pass. Choice, score and noul. A research model, not a medical device.
An independent Jev-shaped reproduction on DeBERTa-v3-large. One state and any number of choice, score and yes/no questions go in, and a calibrated distribution per question comes out of one forward pass. Public gold labels only.
Decides
choice, score, noul
choice, score, noul, classify
Architecture
docto-decision
open-jev
Fine-tuned from
qwen/qwen3.5-4b
microsoft/deberta-v3-large
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
88.9%
85.4%
Calibration error
0.079
0.022
Valid action rate
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Median latency
47 ms
28 ms
p95 latency
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Evaluation suite
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between docto-decision and open-jev-deberta-v3-large?
docto-decision is from Bofeng Huang and open-jev-deberta-v3-large from Kotoba Labs. Both have open weights you can download and run. Both answer choice, score and noul questions. Only open-jev-deberta-v3-large answers classify. open-jev-deberta-v3-large is the smaller model, at 434M parameters to 4.7B.
Which is more accurate, docto-decision or open-jev-deberta-v3-large?
They report on different suites — docto-decision 88.9% on Docto Decision Bench fr v0.1 (12 tasks, mostly silver labels; the maker's own benchmark), open-jev-deberta-v3-large 85.4% on Kotoba held-out test, seen question types (banking77, SST-5, BoolQ) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, docto-decision or open-jev-deberta-v3-large?
docto-decision: Free (open weights). open-jev-deberta-v3-large: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, docto-decision or open-jev-deberta-v3-large?
By their publishers’ figures, open-jev-deberta-v3-large answers in about 28 ms at the median and docto-decision in about 47 ms — measured on different hardware, so treat it as a rough guide.
Can I run docto-decision or open-jev-deberta-v3-large locally?
Yes, both: systemone pull bofeng-huang/docto-decision and systemone pull kotoba-labs/open-jev-deberta-v3-large download the weights.
Docto Decision Bench fr v0.1 (12 tasks, mostly silver labels; the maker's own benchmark)
Kotoba held-out test, seen question types (banking77, SST-5, BoolQ)
