I Cut My AI Bill in Half With Open Source LLMs Heres How

Dev.to / 6/17/2026

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Key Points

The author says their SaaS was spending about $800/month on GPT-4o API calls for tasks that often didn’t require the most advanced frontier model.
After switching to open-source LLMs via the Global API (access to 184 models), they report reducing AI inference costs dramatically, with pricing as low as $0.01–$3.50 per million tokens depending on the model.
They describe a “bill shock” moment when summarizing ~2,000-word support tickets at high volume made inference costs exceed what they were paying themselves.
The article explains how they iteratively tested open-source models for production readiness and landed on a model-mixing approach based on task requirements.
They provide example daily pricing for several models (e.g., DeepSeek and Qwen variants, GLM-4 Plus), showing differing input/output and context-length costs to optimize spending.

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