Cua has simultaneously open-sourced two S1 models, and also invited Jev to join the same benchmark test.
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Beating AI Express: Open-source computer-use infrastructure project Cua has open-sourced two S1 models specialized for computer use decision-making, and launched Cua-Bench-S1, a benchmark that evaluates models like Jev separately. This benchmark does not allow models to plan on their own. Each task provides the current interface and a set of pre-selected actions (e.g., "fill email", "check agree", "click submit", "skip"), with the model making only one selection per task. No re-screening of the interface or failure retries are permitted. This setup tests one core question purely: what is the next step? The two open-sourced models take different approaches: The Nano version has only ~855,000 trainable parameters, trained from scratch, and is specialized for scoring candidate actions. The 4B version uses Qwen3.5-4B as its base model, fine-tuned into the same "multiple-choice model" framework. The former prioritizes minimal size and speed, while the latter leverages the large model’s inherent comprehension for stronger generalization. Beyond common tasks like form filling, login, and search, the benchmark also includes security judgment, chess, Doom, and JevBench. The latter tasks are intentionally excluded from the models’ training data, to test their ability to make correct decisions outside familiar scenarios.
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