An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
Native MLX FP16 conversion of Laya's multilingual checkpoint (mmBERT) for Apple silicon, with a 1,024-token context. The base for multilingual fine-tunes in Laya Studio.
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
kev
laya
Fine-tuned from
qwen/qwen3.5-4b-base
convaiinnovations/laya-multilingual
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
83.8%
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Calibration error
0.042
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Valid action rate
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Median latency
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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 kev and laya-multilingual-mlx?
kev is from Jared Palmer and laya-multilingual-mlx from aac6fef. Both have open weights you can download and run. Both answer choice, score and noul questions. Only kev answers classify and route. kev reads up to 8K tokens of state, against 1K tokens for laya-multilingual-mlx. laya-multilingual-mlx is the smaller model, at 322M parameters to 4.0B.
Which is more accurate, kev or laya-multilingual-mlx?
Only kev publishes an accuracy figure (83.8% on transfer-v4 (locked, out of domain)); laya-multilingual-mlx does not, so there is no comparison to make without your own test.
Which is cheaper, kev or laya-multilingual-mlx?
kev: Free (open weights). laya-multilingual-mlx: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run kev or laya-multilingual-mlx locally?
Yes, both: systemone pull jared-palmer/kev and systemone pull aac6fef/laya-multilingual-mlx download the weights.
