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.
Upstage's structured decision model, a System One endpoint on Solar Mini 4. Returns a choice, a score or a yes/no answer with a probability read from the model, in one forward pass, on the same /v1/systemone schema as Jev.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
julia
solar
Fine-tuned from
jhu-clsp/mmbert-small
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License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
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Upstage
Input price
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$0.10/MTok
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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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 solar-decide?
julia-1 is from Supersonic Labs and solar-decide from Upstage. julia-1 has open weights you can download and run; solar-decide is only available as a hosted API. Both answer choice, score, noul, classify and route questions. solar-decide reads up to 512K tokens of state, against 8K tokens for julia-1. julia-1 is licensed apache-2.0; solar-decide, proprietary.
Which is more accurate, julia-1 or solar-decide?
Only julia-1 publishes an accuracy figure (73.2% on typed-decisions test set (400 cases, 2,000 questions)); solar-decide does not, so there is no comparison to make without your own test.
Which is cheaper, julia-1 or solar-decide?
julia-1: Free (open weights). solar-decide: $0.1 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run julia-1 or solar-decide locally?
julia-1 yes — systemone pull supersonic-labs/julia-1 downloads its weights. The other is only served as a hosted API.
Evaluation suite
typed-decisions test set (400 cases, 2,000 questions)
