OpenAI's Decisions API: Stop Paying for Words You Don't Read

Here's a pricing model I didn't expect to see: an LLM API that charges you $0 for output tokens.

OpenAI's Decisions API entered public beta on October 6, 2026. It doesn't generate text. It returns decisions — a probability, a choice, or a score — and bills you only for what you send in. Here's what it actually does, where the math works, and where OpenAI's claims need a second look.

What it is

A dedicated endpoint — POST /v1/decisions — that turns text or images into a machine-usable answer. You define the question; the API returns one of three typed shapes:

• Predicate: a 0-to-1 probability that a condition is true ("is this message urgent?")
• Choice: one option picked from your fixed list, with confidence scoring ("route to: billing / support / shipping / account")
• Score: a rating against ordered severity levels

No prose to parse. No "this appears to be a billing-related issue, so I recommend..." paragraph that your code then has to regex into an action. The answer arrives already structured.

It runs on gpt-6-luna — currently the only supported model. Inputs can be text, images, or both, though images must be inline base64 data URLs (up to 128 per request); hosted links and uploaded file IDs are refused.

The pricing: input-only billing

This is the part worth doing math on:

• $0.10 per 1M input tokens
• $0 output tokens. $0 cache reads. $0 cache writes.

Compare with calling gpt-6-luna through the normal endpoints: $0.10 input / $0.50 output. For classification-style workloads — where the answer is a label, not an essay — the output bill was always the insult added to injury. Decisions API removes it entirely.

One analysis put it at roughly one-fifth the cost of standard Luna pricing for classification workloads with short answers. Your mileage depends on your input/output ratio, but the direction is unambiguous: if your LLM calls return three tokens of verdict, you were overpaying.

Two asterisks, both from OpenAI's own docs: regional processing premiums and long-context input multipliers apply, with no published figures. Price it on your actual traffic, not the headline.

The 10x speed claim — handle with care

OpenAI says Decisions returns answers "about 10x faster than the Responses API." That number appears in the launch materials with no accompanying benchmark, no per-call compute disclosure, and no head-to-head accuracy comparison between /v1/decisions and the same gpt-6-luna model called through the Responses API.

Faster is plausible — skipping autoregressive text generation for a typed scalar should be cheaper compute. But "10x faster at what accuracy?" is unanswered. A decision API that returns the wrong choice quickly is worse than a slow one that's right. OpenAI's own guidance says to set thresholds from your labeled examples, which is the honest version of "validate this yourself."

Treat the 10x as marketing until someone publishes numbers. The pricing, at least, is verifiable arithmetic.

Decisions vs Structured Outputs vs function calling

OpenAI's own guide draws the lines:

• Decisions API: you need a verdict — classify, route, score, gate. The answer IS the output.
• Structured Outputs (Responses API): you need extracted fields or a written explanation alongside structure.
• Function calling: you need the model to trigger a tool with arguments.

If you find yourself prompting "respond with ONLY the word billing" and then stripping whitespace and lowercasing — that's a Decisions API call wearing a Chat Completions costume. Migrate it.

Where it fits

Good fit:

• Content moderation and triage queues (classify → route → act)
• Agent tool-routing: "which tool handles this request?" as a typed choice
• Any pipeline where an LLM currently returns a label you parse
• Compliance-sensitive flows — it ships with Zero Data Retention support, HIPAA eligibility, and US/EU data residency, which makes it a plausible drop-in for gating flows that previously stitched JSON-schema prompts onto Chat Completions

Watch out:

• Beta status — GA is "coming weeks," no firm date
• Single model (gpt-6-luna) — no fallback if Luna misbehaves on your domain
• Image inputs are inline-only — if your pipeline serves hosted URLs, you add a fetch-and-encode step
• Undisclosed regional/long-context multipliers — model your costs on measured traffic

The bigger pattern

Decisions API is OpenAI unbundling the LLM. For years the industry sold one primitive — "generate text" — and developers built classifiers, routers, and scorers out of prose plus parsing. Now the primitives are splitting: text generation for what needs text, typed decisions for what needs decisions, each priced on what it actually costs to serve.

Anthropic did the same split from the other direction this month: Haiku 5.5 for volume, Opus 5.5 for frontier reasoning. The era of one-model-fits-all is ending. The winners will be the teams that route each call to the cheapest primitive that can do the job.

TL;DR

• Decisions API (public beta, Oct 6): POST /v1/decisions, returns probability / choice / score instead of prose
• Pricing: $0.10/1M input, $0 output — roughly 5x cheaper than standard Luna for classification workloads
• 10x-faster claim is unverified — validate accuracy on your own labeled data
• Use it when the answer is a verdict; keep Structured Outputs when you need explanation + structure
• Beta caveats: single model, inline images only, undisclosed regional multipliers

Sources: OpenAI developer forum announcement (Oct 6, 2026), OpenAI Decisions guide and pricing page, AI Weekly, FourWeekMBA, Ground Truth. Speed and accuracy claims are OpenAI's; no independent benchmark was available at writing time.