A family of open System One models by Mark Marosi, decider-0.8b, decider-2b, decider-4b and decider-35b-a3b on Qwen3.5 bases, that softmax letter logits at an answer slot. This page carries decider-2b v11.
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
decider
laya
Fine-tuned from
qwen/qwen3.5-2b-base
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
75.2%
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Calibration error
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Valid action rate
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Median latency
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39.5 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 decider and laya?
decider is from Mapika and laya from Convai Innovations. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. decider reads up to 32K tokens of state, against 512 tokens for laya. laya is the smaller model, at 421M parameters to 1.9B.
Which is more accurate, decider or laya?
Only decider publishes an accuracy figure (75.2% on Decider regression set, 28 held-out tasks (decider-2b v11)); laya does not, so there is no comparison to make without your own test.
Which is cheaper, decider or laya?
decider: Free (open weights). laya: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run decider or laya locally?
Yes, both: systemone pull mapika/decider and systemone pull convai-innovations/laya download the weights.
