We Tracked 1M LLM API Calls — 60% Were Wasting Money on the Wrong Model

Dev.to / 6/11/2026

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Key Points

An analysis of the first 1M LLM API calls across Tokonomics (47 tenants, 9 providers, dozens of models) found teams often default to GPT-4o for nearly everything, even when simpler tasks are involved.
The article argues that a large share of production calls (about 60–70%) do not require a frontier model, and switching classification tasks from GPT-4o to DeepSeek V3 can cut input token costs dramatically (18x).
It recommends using model routing combined with prompt caching to reduce total LLM spend by an estimated 80–95%.
Despite rising AI usage costs—average monthly spend reaching $85,500 per company in 2025—the findings suggest many teams do not actively audit which models are used for which workloads.
The piece warns that “prototype defaults” can persist into production, driving unnecessary costs when cheaper models can deliver equivalent quality for specific components.

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