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.
A 144M-parameter System One model on the multilingual mmBERT-small encoder. Takes a state, a question and 2 to 20 options and returns one decision with probabilities for choice, score and yes/no questions, on a CPU.
Decides
choice, score, noul
choice, score, noul, classify, route
Architecture
docto-decision
julia
Fine-tuned from
qwen/qwen3.5-4b
jhu-clsp/mmbert-small
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%
73.2%
Calibration error
0.079
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Valid action rate
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Median latency
47 ms
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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 julia-1?
docto-decision is from Bofeng Huang and julia-1 from Supersonic Labs. Both have open weights you can download and run. Both answer choice, score and noul questions. Only julia-1 answers classify and route. julia-1 is the smaller model, at 144M parameters to 4.7B.
Which is more accurate, docto-decision or julia-1?
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), julia-1 73.2% on typed-decisions test set (400 cases, 2,000 questions) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, docto-decision or julia-1?
docto-decision: Free (open weights). julia-1: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run docto-decision or julia-1 locally?
Yes, both: systemone pull bofeng-huang/docto-decision and systemone pull supersonic-labs/julia-1 download the weights.
Docto Decision Bench fr v0.1 (12 tasks, mostly silver labels; the maker's own benchmark)
typed-decisions test set (400 cases, 2,000 questions)
