Frontier Infra's open decision model. A LoRA merged into Qwen3.8-27B (thinking off) that answers one typed question per forward pass with a probability over the option labels, served through AINode's TypeSafe-compatible /v1/systemone.
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
jebadiah
laya
Fine-tuned from
qwen/qwen3.8-27b
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
86.6%
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Calibration error
0.113
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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 jebadiah and laya?
jebadiah is from Frontier Infra and laya from Convai Innovations. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. laya is the smaller model, at 421M parameters to 27B.
Which is more accurate, jebadiah or laya?
Only jebadiah publishes an accuracy figure (86.6% on JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier); laya does not, so there is no comparison to make without your own test.
Which is cheaper, jebadiah or laya?
jebadiah: Free (open weights). laya: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run jebadiah or laya locally?
Yes, both: systemone pull frontier-infra/jebadiah and systemone pull convai-innovations/laya download the weights.
Evaluation suite
JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier