OpenAI Decisions API Is Now GA: 100ms Agent Routing

OpenAI made its Decisions API generally available on October 22, a classification endpoint built on GPT-6 Luna that returns typed answers in 100–180 milliseconds and accepts up to 400 developer-defined questions per request to POST /v1/decisions. The API supports predicate, choice and score question types over text, JSON and image inputs, and Speak, a language learning app, cut time between actions from 1.4 seconds to 0.13 seconds after replacing a model call with it. OpenAI prices the Decisions API at $0.10 per million input tokens versus $0.042 per million for incumbent TypeSafe Jev, which is text-only, and the Decisions API currently offers no caching.

OpenAI made its Decisions API generally available on October 22 — a classification endpoint built on GPT-6 Luna that returns typed answers in 100–180 milliseconds. This is not a general language model. You give it a finite list of possible answers and it picks one, which makes it purpose-built for content moderation, request routing, and the per-step decision-making inside agent loops. Three Things You Can Ask It The API exposes three question types. A predicate question returns a probability between 0 and 1 — useful for yes/no conditions like “does this image contain source code?” A choice question selects one option from a developer-defined list and returns per-option probabilities alongside a confidence score. A score question rates an input against a rubric of 2–10 ordered levels and returns the probability-weighted average. Each request goes to POST /v1/decisions with the model set to gpt-6-luna . You define up to 400 questions per request. Inputs can be text, JSON, or images — passed as base64 or a public URL. The response is an answers array keyed by the developer-assigned question name, not prose. The Speed Numbers A standard Responses API call to GPT-6 Luna runs 1–3 seconds. The Decisions API runs at 100–180ms. OpenAI’s own DevDay slide put it at 150ms versus 1,600ms — roughly a 10x improvement. In production, Speak the language learning app replaced a model call with the Decisions API and cut time between actions from 1.4 seconds to 0.13. That is a 10.8x speedup on a real user-facing interaction. When your agent needs to make dozens of routing decisions per task, that difference accumulates fast. Where It Fits in Agent Architecture The pattern the Decisions API is built for has a name: planner-executor. A capable frontier model does the planning — breaking down a goal, deciding strategy, handling ambiguity. Then a fast, cheap model handles the per-step routing: which tool to call next, which queue to send this to, whether a condition is met. The Decisions API is designed for that executor role. This separation matters because it lets you control costs and latency independently. The expensive model runs infrequently; the fast model runs constantly. Until now, developers had to approximate this with JSON schemas and post-processing. OpenAI is making it a first-class endpoint. The Price and the Comparison You Need to Make The Decisions API costs $0.10 per million input tokens. TypeSafe Jev — the incumbent that OpenAI is clearly positioning against — costs $0.042 per million input tokens. Jev also offers free output tokens. At scale, the difference is not trivial: 1 million 500-token classifications cost about $50 with OpenAI versus $21 with Jev. Where OpenAI wins is image inputs. Jev is text-only. If your classification task involves screenshots, product photos, or documents with visual content, the Decisions API is the only option in this category. For pure-text routing, Jev is still faster and cheaper — developer benchmarks put Jev’s P50 latency at 210ms versus OpenAI’s 100–180ms range, with better accuracy on judgment-heavy text tasks. This is not a knock on OpenAI’s launch. It is a market that is expanding quickly — MarkTechPost counted 20 Jev alternatives as of October 17. More competition means better tools, and OpenAI entering validates the category TypeSafe built. One Limitation Worth Knowing There is currently no caching for the Decisions API. For high-volume classification with repeated or similar inputs, that will matter. OpenAI says caching may come later, but it is a real gap compared to caching-friendly setups on the Responses API. Who Should Test It First If you are building agent workflows and classification is a bottleneck, the Decisions API is worth a direct test. The official documentation https://developers.openai.com/api/docs/guides/decisions has the request schema and question type reference. For a hands-on walkthrough, DataCamp’s tutorial https://www.datacamp.com/tutorial/open-ai-decisions-api-tutorial covers the three question types with working examples. If you are comparing it against Jev specifically, Firecrawl’s benchmark breakdown https://www.firecrawl.dev/blog/openai-decisions-api-vs-jev has the data you need. The GA pricing is live; TechCrunch’s coverage https://techcrunch.com/2026/10/22/openai-makes-its-jev-competitor-widely-available-as-decision-model-competition-heats-up/ has the full product timeline.