OpenAI's GPT-5.6 builder guide shows how to run frontier agents at a fraction of the cost

GPT-5.6 构建者指南：如何以更低成本实现前沿智能体性能

OpenAI published a builder's guide for GPT-5.6, showing how startups use cheaper models like Luna and Terra for agent workloads. Hex dropped GPT-5.6 into their harness and got best results at low reasoning effort—the model didn't chase bad leads and used fewer tokens. Hypha kept 98% of GPT-5.5's extraction accuracy at 1/18 the cost. Browser Use ran 106 hard browser tasks: Luna hit 78% for $14, while the current SOTA model reached 80% for $235. On BrowseComp, GPT-5.6 Luna (Extra High) scored 84.04% at $1.33; three months ago GPT-5.5 (Extra High) scored 84.36% at $33.27. The guide also details three new API primitives: persisting reasoning across turns, native multi-agent orchestration, and programmatic tool calling for deterministic work. The post does not disclose release dates or regional availability.

Why it matters: An official builder's guide from OpenAI with real startup case studies and concrete cost/performance tradeoffs — useful for developers. But it's a product best-practices doc, not a model launch or research breakthrough, so importance caps at recommended-reading level.