A training-free layer that turns an open LLM into a decision model. It reads typed choice, yes/no and score answers from one prefill, removes option-order bias with no labels and, from a few hundred labels, calibrates or fits a closed-form head. Weights stay untouched.
Unofficial NoulXP package of Convai Innovations' Laya multilingual (Apache-2.0), fp32-o23: checked against the model's own answers, none changed. Not made by Convai Innovations.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
anyjev
laya
Fine-tuned from
qwen/qwen3-8b
convai-innovations/laya
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
77.1%
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Calibration error
0.034
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Valid action rate
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Median latency
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44.9 ms
p95 latency
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742 ms
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 anyjev and laya-multilingual-noulxp?
anyjev is from Nokia and laya-multilingual-noulxp from Convai Innovations. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. laya-multilingual-noulxp is the smaller model, at 322M parameters to 8.0B.
Which is more accurate, anyjev or laya-multilingual-noulxp?
Only anyjev publishes an accuracy figure (77.1% on LocalLLaMA/typed-decisions (2,000 held-out decisions), L2 with 300 labels per question); laya-multilingual-noulxp does not, so there is no comparison to make without your own test.
Which is cheaper, anyjev or laya-multilingual-noulxp?
anyjev: Free (open weights). laya-multilingual-noulxp: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run anyjev or laya-multilingual-noulxp locally?
Yes, both: systemone pull nokia/anyjev and systemone pull convai-innovations/laya-multilingual-noulxp download the weights.
LocalLLaMA/typed-decisions (2,000 held-out decisions), L2 with 300 labels per question
Measured by System One Models on 2026-10-05: one question per request, 4 threads of a Xeon Gold 6342
