Multi-Model API Cost Governance with the Inference Router
DigitalOcean's Inference Router (part of Inference Engine, public preview since April 2026) lets you route LLM API calls to different models based on task complexity, reducing inference costs without changing application code. The tutorial builds a three-path router for a SaaS support backend: a cheap classifier path using openai-gpt-oss-20b, a quality-sensitive Q&A path using Claude Sonnet 4.6 with Manual Ranking, and a reasoning path using GPT-5. All paths are invoked via a single OpenAI-compatible endpoint. Per-request cost signals are readable from response headers. At a traffic split of 700K classify, 250K Q&A, and 50K reasoning requests/month, the routed setup costs $2,850/month vs. $4,716 for a hardcoded Claude Sonnet 4.6 baseline — a 39.6% saving. The tutorial also covers session pinning with X-Model-Affinity for KV-cache warmth across multi-turn conversations, observability via the Analyze dashboard, and common troubleshooting scenarios including credential team mismatches and reasoning token budget issues.