Behavior Strength and Deployment Readiness Across Six Frontier-Model Deployments: A First-Party Observational Study in Microsoft Foundry

Abstract

Model benchmarks usually score answers after a response exists. Production applications face another question: how often does a usable answer reach the caller? This first-party observational study evaluates six frontier-model deployments accessed through Microsoft Foundry and separates behavior strength on eligible answers from deployment readiness across the full caller-experienced matrix.

Claude Sonnet 5 achieved the highest deployment readiness at 89.85. GPT-5.6 Sol achieved 100.00 behavior strength on eligible answers, but 41 provider blocks reduced its readiness to 76.44. The result shows why answer quality and reliable delivery should be measured separately.