Qwen3.5-4B with a merged rank-16 LoRA distilled from 17,408 teacher questions and 30,000 public training rows, read out as a temperature-scaled softmax over answer-letter logits. Also in 9B, 2B and GGUF.
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
jevk5
laya
Fine-tuned from
qwen/qwen3.5-4b
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
78.4%
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Calibration error
0.035
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Valid action rate
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Median latency
13.2 ms
39.5 ms
p95 latency
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Evaluation suite
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 jevk5 and laya?
jevk5 is from Alibi Serikbay 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 4.0B.
Which is more accurate, jevk5 or laya?
Only jevk5 publishes an accuracy figure (78.4% on JevBench public hard tier); laya does not, so there is no comparison to make without your own test.
Which is cheaper, jevk5 or laya?
jevk5: Free (open weights). laya: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, jevk5 or laya?
By their publishers’ figures, jevk5 answers in about 13.2 ms at the median and laya in about 39.5 ms — measured on different hardware, so treat it as a rough guide.
Can I run jevk5 or laya locally?
Yes, both: systemone pull alibi-serikbay/jevk5 and systemone pull convai-innovations/laya download the weights.
