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AI routing: Use smaller models for efficiency, save costs

A more cost-effective and efficient approach to using large language models involves routing different types of inputs to specialized, smaller models instead of always sending them to a single, powerful frontier model. An orchestrator small language model can classify inputs like code, specific languages, or support tickets and direct them to appropriate specialist models. This strategy reduces costs and improves speed, especially at scale, by reserving the most powerful models for complex tasks or final decision-making. Additionally, specialist models should output machine-readable structured data for efficient consumption by downstream models, rather than human-readable text. AI

IMPACT Optimizing AI usage with specialized models can significantly reduce operational costs and improve response times for organizations at scale.

RANK_REASON The item discusses a strategy for optimizing AI model usage, focusing on efficiency and cost savings through model routing, rather than announcing a new model or research breakthrough.

Read on dev.to — LLM tag →

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  1. dev.to — LLM tag TIER_1 English(EN) · Jinav Shah ·

    You're probably using AI wrong. And it's costing you more than you think.

    <p>Most companies today have one AI setup: send everything to the most powerful model available. Pay the bill. Repeat.</p> <p>It works. But it's expensive, slower than it needs to be, and honestly — a bit like hiring a surgeon to change a lightbulb.</p> <h2> The problem nobody ta…