AutoTrust's student of TypeSafe Jev 1.13. A frozen Qwen3.8-27B plus a 108.9M-parameter decision block trained on Jev's own output distributions; one set of weights answers typed questions in one pass (System 1) or generates text with the untouched base (System 2).
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
choice, score, noul, classify, route
Architecture
blocks-of-experts
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
88.7%
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Calibration error
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Valid action rate
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Median latency
137 ms
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 jev-27b and laya?
jev-27b is from AutoTrust AI Lab and laya from Convai Innovations. Both have open weights you can download and run. Both answer choice, score and noul questions. Only laya answers classify and route. laya is the smaller model, at 421M parameters to 27B.
Which is more accurate, jev-27b or laya?
Only jev-27b publishes an accuracy figure (88.7% on JevBench public set (231 items), family-macro score, maker's run); laya does not, so there is no comparison to make without your own test.
Which is cheaper, jev-27b or laya?
jev-27b: Free (open weights). laya: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, jev-27b or laya?
By their publishers’ figures, laya answers in about 39.5 ms at the median and jev-27b in about 137 ms — measured on different hardware, so treat it as a rough guide.
Can I run jev-27b or laya locally?
Yes, both: systemone pull autotrust-ai/jev-27b and systemone pull convai-innovations/laya download the weights.
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Evaluation suite
JevBench public set (231 items), family-macro score, maker's run
