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.
TokenRhythm's prefill-only decision model for agent workflows. Built on its NeoHorse-1-4B (a Qwen3.5-4B derivative), it predicts Choice, Noul and Score answers over application-defined options without generating text, with optional single-image input.
Decides
choice
choice, score, noul, classify, route
Architecture
cua-s1
neohorse
Fine-tuned from
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tokenrhythm/neohorse-1-4b
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%
75.3%
Calibration error
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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 cua-s1-forms and neohorse-jev?
cua-s1-forms is from Cua and neohorse-jev from TokenRhythm. Both have open weights you can download and run. Both answer choice questions. Only neohorse-jev 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; neohorse-jev, apache-2.0.
Which is more accurate, cua-s1-forms or neohorse-jev?
They report on different suites — cua-s1-forms 100.0% on 196-decision evaluation on real forms, neohorse-jev 75.3% on JevBench public set (231 items), vLLM, maker's run — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, cua-s1-forms or neohorse-jev?
cua-s1-forms: Free (open weights). neohorse-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run cua-s1-forms or neohorse-jev locally?
Yes, both: systemone pull cua/cua-s1-forms and systemone pull tokenrhythm/neohorse-jev download the weights.
Evaluation suite
196-decision evaluation on real forms
JevBench public set (231 items), vLLM, maker's run
