Cactus Hybrid post-trains small on-device models to know when they are wrong. Every answer carries a confidence score returned as structured data rather than parsed out of the answer text, so an application can answer locally when confidence is high and hand the query to a larger cloud model when it is low.
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Send low-confidence answers on to a bigger model
Answer on-device and avoid an API call entirely
Trade a small accuracy drop for a much lower bill
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