GPT-6 Luna
−30% vs OpenAI
AzureOpenAIThe cheapest of the GPT-6 line, built for volume: a million-token window at ten cents a million. For classifying, extracting and summarising at scale rather than for hard reasoning.
The real OpenAI model
Same weights, same API, same answers. We change only how you pay for it: one key for every maker, one bill, no separate account to open. Every figure on this page comes from OpenAI’s own page — check it.
Maker's own pagePrice
input / output · per 1M tokensThe same model and the same answers through both. The daily discount applies to eligible requests within the displayed token limit.
Azure
−30%Only on FlintBeam−30% on requests up to 250,000 tokens
Direct on Azure: $0.10 / $0.50
Daily discount. Today's price can change.
OpenAI
Official price
More pricing details: speeds and very long prompts
| Speed | AzureUp to 250,000 tokens | OpenAIAbove 250,000 tokens |
|---|---|---|
| Flex · slower | $0.05 / $0.25 | |
| Priority · faster | — | $0.20 / $1.00 |
Above 272,000 input tokens through OpenAI, the whole request costs here: $0.20 / $0.75 (Standard); $0.10 / $0.38 (Flex · slower); $0.40 / $1.50 (Priority · faster)
Context
1,050,000
up to 128,000 out
128,000 by default here
Modalities
Released
—
Knows up to May 18, 2026
What it would cost you
1000 tokens is roughly 750 English words.
How it is served
Requests are retried automatically if a provider is unavailable.
Similar models
Models built for the same kind of work, at a similar price.
Eligible models may have a daily discount below the maker's price. Daily discounts apply to eligible models and can change from day to day.
Use it from your code
from openai import OpenAI
# Works with the official openai package (pip install openai)
client = OpenAI(
base_url="https://api.flintbeam.com/v1",
api_key="sk-live-your-api-key"
)
response = client.chat.completions.create(
model="openai/gpt-6-luna",
messages=[
{"role": "system", "content": "You are an experienced software engineer."},
{"role": "user", "content": "Describe the architecture of a distributed cache."}
],
temperature=0.7,
max_tokens=1500
)
print(response.choices[0].message.content)