The first System One model. Reads a state, answers typed Choice, Score and Noul questions in one call with calibrated probabilities, and generates no text. Closed weights, served by TypeSafe AI.
StartLux's decision family in five sizes, 0.8B to 27B. All questions in a request are answered in one forward pass, with a probability for every option, through a TypeSafe /v1/systemone-compatible server that records CUDA graphs for short requests.
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
jev
startlux-decision
Fine-tuned from
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License
proprietary
cc-by-nc-4.0
Availability
Hosted API
Open weights
Hosted by
TypeSafe AI
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Input price
$0.042/MTok
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Decision accuracy
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88.3%
Calibration error
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Valid action rate
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Median latency
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26 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 jev and startlux-decision?
jev is from TypeSafe AI and startlux-decision from StartLux. jev is only available as a hosted API; startlux-decision has open weights you can download and run. Both answer choice, score and noul questions. Only jev answers classify and route. jev is licensed proprietary; startlux-decision, cc-by-nc-4.0.
Which is more accurate, jev or startlux-decision?
Only startlux-decision publishes an accuracy figure (88.3% on JevBench public set (231 items; 204 correct), maker's run); jev does not, so there is no comparison to make without your own test.
Which is cheaper, jev or startlux-decision?
jev: $0.042 / $0 per 1M. startlux-decision: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jev or startlux-decision locally?
startlux-decision yes — systemone pull startlux/startlux-decision downloads its weights. The other is only served as a hosted API.
Evaluation suite
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JevBench public set (231 items; 204 correct), maker's run
