systemonemodels.pro

GPT-6 Luna price

"GPT 6 luna price" is one of the few queries in this wave where our captured sources actually contain a number. The directory description states it flatly: "standard pricing of $0.10 input / $0.50 output per 1M tokens" for OpenAI's GPT-6 Luna vendor claim. We will report that anchor — with its source, its limits, and a healthy instruction: confirm on OpenAI's official pricing page before making any decision, because the directory, not us, is vouching for the figure. Our tracker logged the phrase at roughly 0.08× the GPTs baseline and rising, with four dedicated pages in the field observed. Labels: vendor claim / observed / analysis.

Who (and what) is GPT-6 Luna

Luna is the sibling of Sol: OpenAI announced the two together in "Introducing GPT-6 Sol and Luna" on openai.com observed. Directory descriptions position the pair as the family's affordable workhorses — Sol described as "low-cost, high-performance," with a price anchor now attached to Luna by the directory entry for this very query vendor claim. The family context, and the successor question around it, live on GPT Sol 6.1 and GPT-6.1 Sol vs Astra.

The price anchor, read carefully

ComponentDirectory-anchored figureStatus
Input tokens$0.10 per 1M tokens vendor claimDirectory description, captured October 2026 — not verified against OpenAI directly analysis
Output tokens$0.50 per 1M tokens vendor claimSame source, same caveats analysis
Label"Standard price" per the description vendor claimStandard ≠ only: promotional, batch or tiered rates can differ analysis
Final authorityOpenAI's official pricing page — always; the directory anchor is a starting point, not a quote analysis

Two features of the anchor are worth noting because they match the common shape of API pricing analysis: output bills at roughly 5× input, and the absolute levels are low — consistent with the family's "affordable workhorse" positioning across descriptions vendor claim. If the anchor is right, a workload writing a million tokens of output costs fifty cents; the expensive part of most real applications remains the input side, where context and tool output accumulate analysis.

From a rate to a bill

Rates are trivia; bills are decisions. The workable path analysis:

  1. Verify the anchor against OpenAI's official pricing page — one click, and you've converted a vendor claim into a fact analysis.
  2. Split your traffic into input and output estimates — they bill 5:1 apart per the anchor analysis.
  3. Model the month in our API cost calculator, including retries and context growth analysis.
  4. Compare at equal workloads — pull sibling rates (Sol's, Astra's) from official pages and rerun the same traffic; see GPT-6 Sol vs 5.6 Sol for why this family's comparisons are increasingly about price analysis.

For the Anthropic-side pricing questions, our sibling pages Sonnet 5.5 price and Sonnet 5.5 cost apply the same labeled-claims discipline.

Related pages

GPT-6 Luna price FAQ

Is $0.10 / $0.50 per million the real price?

It is the directory description's "standard price" vendor claim — a credible starting anchor that must be confirmed on OpenAI's official pricing page; we cannot and do not guarantee it analysis.

Is Luna cheaper than Sol?

No verified side-by-side exists in our captures; the descriptions position both as the affordable half of the family. Compare official rates at equal workloads before concluding analysis.

Does the consumer ChatGPT subscription cost the same?

Almost certainly not — per-token API rates and flat consumer plans are different products. Don't compare one to the other analysis.

Why trust your anchor over other blogs' tables?

You shouldn't trust either blindly — the difference is we tell you the anchor's source and shelf life, then send you to the official page. That's the whole discipline analysis.

This page is descriptive and independent, last reviewed October 8, 2026. Not affiliated with OpenAI. "OpenAI" and "GPT" are trademarks of their respective owners; the price anchor is a third-party directory claim reported with attribution and not independently verified.