Fireworks AI

What this post added

This post introduces the concept of the "Agent Execution Tax" and a "Deployment Readiness Scorecard" to evaluate LLMs for agentic AI. It details a benchmark of 720 browser agent runs across four LLMs, measuring structured output reliability and step efficiency. The analysis quantifies the "Agent Execution Tax" as the ratio of wasted inference to productive inference, demonstrating how malformed JSON output and retries significantly inflate costs and latency. It also provides a per-site analysis and model profiles (GLM-5, MiniMax M2.5, Kimi K2.5) based on these metrics, emphasizing the importance of reliable execution infrastructure in agent deployments.