
In the competitive landscape of AI, managing API costs without sacrificing output quality is critical. Our project introduces a highly efficient, hybrid token-routing agent designed specifically to minimize cloud API expenses while maximizing local hardware capabilities. The agent intercepts user queries and performs instant, lightweight classification to determine the complexity of the task. Trivial and straightforward queries are immediately routed to small, lightning-fast local models like Llama 3.2 3B. This ensures instant responses and exactly zero API cost for everyday interactions. For complex coding, logic, and reasoning tasks, the agent dynamically activates a Zero-Cost Multi-Agent Committee. Instead of immediately escalating the task to an expensive cloud model, it spins up multiple local models (such as Gemma, Qwen, and Llama) to generate independent drafts. A local master synthesizer model then reviews all the drafts, cross-references the logic, and synthesizes a highly-accurate final response. Only in the rare scenario where the local committee fails or produces a low-confidence answer does the agent gracefully fall back to the Fireworks AI API. This tiered architecture ensures users get the best possible answers while keeping API token usage as close to absolute zero as physically possible.
13 Jul 2026