According to TechCrunch AI's coverage, Smallest.ai's strategy hinges on a two-model future: a small, fast voice model for interaction and a larger LLM for complex problem-solving. This architectural split makes intuitive sense, but the real test will be whether the specialized model can handle the nuance and unpredictability of human conversation without constantly deferring to its larger, slower counterpart. The focus on enterprise customer support is a logical beachhead, but the ultimate challenge may be scaling the 'knowledge base' of the small model beyond scripted scenarios.
If the handoff to the LLM becomes too frequent, the latency problem simply reappears in a different form. Success will depend less on raw speed and more on the model's ability to understand context and intent within a constrained domain.