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.
An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
julia
kev
Fine-tuned from
jhu-clsp/mmbert-small
qwen/qwen3.5-4b-base
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
73.2%
83.8%
Calibration error
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0.042
Valid action rate
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Median latency
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p95 latency
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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 julia-1 and kev?
julia-1 is from Supersonic Labs and kev from Jared Palmer. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. julia-1 is the smaller model, at 144M parameters to 4.0B.
Which is more accurate, julia-1 or kev?
They report on different suites — julia-1 73.2% on typed-decisions test set (400 cases, 2,000 questions), kev 83.8% on transfer-v4 (locked, out of domain) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, julia-1 or kev?
julia-1: Free (open weights). kev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run julia-1 or kev locally?
Yes, both: systemone pull supersonic-labs/julia-1 and systemone pull jared-palmer/kev download the weights.
Evaluation suite
typed-decisions test set (400 cases, 2,000 questions)
