Developer shares trade-off framework for choosing AI APIs in 2026

A developer who built three production apps on LLMs argues that choosing an AI API in 2026 now hinges on trade-offs rather than finding the single most capable model. They point to latency versus cost, token limits versus context windows, and vendor lock-in versus flexibility as the central considerations. The author lists four production priorities: latency and throughput, cost predictability, context window size, and ease of integration. A legal document summarizer example shows a hybrid approach, using a cheaper model to extract clauses before a larger model writes the summary, which cut latency from 45 to 8 seconds and reduced costs by about 70%. The post also includes a Python sketch of a provider router that routes tasks by complexity to make switching providers easier.