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.
Metask Lab's calibrated decision model in 16 languages. Qwen3.5-4B with a merged LoRA trained with the Nimble candidate-logit objective; one forward pass and a softmax over at most 26 answer-letter logits, with one temperature per question type.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
laya
metask-jev
Fine-tuned from
answerdotai/modernbert-large
qwen/qwen3.5-4b
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
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80.1%
Calibration error
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Valid action rate
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Median latency
39.5 ms
62.8 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 laya and metask-jev?
laya is from Convai Innovations and metask-jev from Metask Lab. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. metask-jev reads up to 4K tokens of state, against 512 tokens for laya. laya is the smaller model, at 421M parameters to 4.5B.
Which is more accurate, laya or metask-jev?
Only metask-jev publishes an accuracy figure (80.1% on JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run); laya does not, so there is no comparison to make without your own test.
Which is cheaper, laya or metask-jev?
laya: Free (open weights). metask-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, laya or metask-jev?
By their publishers’ figures, laya answers in about 39.5 ms at the median and metask-jev in about 62.8 ms — measured on different hardware, so treat it as a rough guide.
Can I run laya or metask-jev locally?
Yes, both: systemone pull convai-innovations/laya and systemone pull metask-lab/metask-jev download the weights.
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Evaluation suite
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JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run
