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-weights System One model from Convai Innovations. A fully fine-tuned ModernBERT-large encoder with a from-scratch decision head that scores one marker per option and answers every question in a single 33–39 ms pass. Runs on your own CPU or GPU.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
julia
laya
Fine-tuned from
jhu-clsp/mmbert-small
answerdotai/modernbert-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
73.2%
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Calibration error
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Valid action rate
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Median latency
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39.5 ms
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 laya?
julia-1 is from Supersonic Labs and laya from Convai Innovations. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. julia-1 reads up to 8K tokens of state, against 512 tokens for laya. julia-1 is the smaller model, at 144M parameters to 421M.
Which is more accurate, julia-1 or laya?
Only julia-1 publishes an accuracy figure (73.2% on typed-decisions test set (400 cases, 2,000 questions)); laya does not, so there is no comparison to make without your own test.
Which is cheaper, julia-1 or laya?
julia-1: Free (open weights). laya: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run julia-1 or laya locally?
Yes, both: systemone pull supersonic-labs/julia-1 and systemone pull convai-innovations/laya download the weights.
Evaluation suite
typed-decisions test set (400 cases, 2,000 questions)
