Developer builds auditable AI cost-modeling pipeline to find cheapest quality-adjusted LLM

A developer behind the Hermes Agent framework built an automated pipeline to answer real cost questions faced by AI agent builders, frustrated by inaccurate online advice. The system uses research agents to pull live, cited token prices and benchmarks, then runs all calculations through an exact-rational math kernel to avoid floating-point errors or LLM-generated arithmetic mistakes. Tested across eight cost scenarios, the pipeline ranked open-weight models by blended cost divided by agentic quality score, with DeepSeek V3.2 via OpenRouter emerging as the top value at roughly $1.49 per quality unit. DeepSeek V4 Flash on Fireworks was flagged as a potentially cheaper alternative pending further quality testing. The full methodology and dataset have been published in a public repository so results can be independently reproduced.