Models trained specifically for browser automation. Higher accuracy, lower latency, fraction of the cost.
Purpose-built for browser tasks. Outperforms general-purpose frontier models at a fraction of the latency and cost.
Read Blog Post →68 seconds per task vs 225-330s for Gemini, Claude, and OpenAI computer use models. Optimized output parsing and batched caching.
53 tasks per dollar vs 2 for Sonnet 4.5. Purpose-built models eliminate the overhead of general-purpose frontier LLMs.
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