A 2.8 MB byte-level transformer for GUI form filling. For each form element it returns one probability per typed option (fill an entity, check, click or skip), using jevlike's option-attention head.
An open System One model from Interfaze AI. A rank-32 LoRA on Qwen3.5-4B reads yes/no, choice and score answers from the logits of one forward pass, returns calibrated probabilities and serves the /v1/systemone API.
Decides
choice
choice, score, noul, classify, route
Architecture
cua-s1
lev
Fine-tuned from
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qwen/qwen3.5-4b
License
mit
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
100.0%
68.9%
Calibration error
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0.115
Valid action rate
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Median latency
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69 ms
p95 latency
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Evaluation suite
196-decision evaluation on real forms
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 cua-s1-forms and lev?
cua-s1-forms is from Cua and lev from Interfaze AI. Both have open weights you can download and run. Both answer choice questions. Only lev answers score, noul, classify and route. cua-s1-forms is the smaller model, at 706K parameters to 4.0B. cua-s1-forms is licensed mit; lev, apache-2.0.
Which is more accurate, cua-s1-forms or lev?
They report on different suites — cua-s1-forms 100.0% on 196-decision evaluation on real forms, lev 68.9% on S1Bench (13 public subsets, macro) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, cua-s1-forms or lev?
cua-s1-forms: Free (open weights). lev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run cua-s1-forms or lev locally?
Yes, both: systemone pull cua/cua-s1-forms and systemone pull interfaze-ai/lev download the weights.
