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.
A Gemma 4 12B fine-tune for typed decisions that also chats and reads images. Ships as GGUF for llama.cpp, holds a 64K context on a 16 GB GPU, and serves /v1/systemone next to /v1/chat/completions.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
laya
winnow
Fine-tuned from
answerdotai/modernbert-large
google/gemma-4-12b-it
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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85.7%
Calibration error
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Valid action rate
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Median latency
39.5 ms
143 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 winnow?
laya is from Convai Innovations and winnow from EldanRing. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. winnow reads up to 64K tokens of state, against 512 tokens for laya. laya is the smaller model, at 421M parameters to 12B.
Which is more accurate, laya or winnow?
Only winnow publishes an accuracy figure (85.7% on JevBench public subset (231 items), Q8_0); laya does not, so there is no comparison to make without your own test.
Which is cheaper, laya or winnow?
laya: Free (open weights). winnow: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, laya or winnow?
By their publishers’ figures, laya answers in about 39.5 ms at the median and winnow in about 143 ms — measured on different hardware, so treat it as a rough guide.
Can I run laya or winnow locally?
Yes, both: systemone pull convai-innovations/laya and systemone pull eldanring/winnow download the weights.
