A rate per million tokens is not a budget. The calculator takes your request volume, prompt size and cache hit rate and gives you a monthly figure.

GPT-6 Luna API pricing (October 2026)

Prices verified 12 Oct 2026

Prompts over 272K tokens bill the whole request at 2x input and cache rates and 1.5x output ($0.20 in / $0.75 out).

Input

$0.100

per 1M tokens

Output

$0.500

per 1M tokens

Cached input

$0.010

per 1M tokens

Batch discount

50% off

async batch endpoint

What it costs at real volumes

A chat-shaped workload: 800 input tokens and 300 output tokens per request, no caching, no batch.

Volume	Per request	Per month	Per year
10K requests/day	$0.00023	$70.01	$840.14	Adjust →
100K requests/day	$0.00023	$700.12	$8,401.44	Adjust →
1M requests/day	$0.00023	$7,001.20	$84.0K	Adjust →

Specifications

Provider: OpenAI
Context window: 1.1M tokens
Max output: 128K tokens
Tier: small
Status: GA
Blended $/1M (3:1): $0.200
Cache break-even hit rate: 22%
Prices verified: 12 Oct 2026

Source: OpenAI pricing. Finitizer is not affiliated with OpenAI.

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Frequently asked questions

How much does GPT-6 Luna cost per 1M tokens?

GPT-6 Luna costs $0.100 per million input tokens and $0.500 per million output tokens at OpenAI list prices. Output is 5.0x the input rate, so the input:output ratio of your workload drives the real cost more than the headline price.

Does GPT-6 Luna support prompt caching?

Yes. Cached input is billed at $0.010 per million tokens, 10x cheaper than uncached input. Cache writes carry a premium, so caching only pays above roughly a 22% hit rate.

What is the batch discount for GPT-6 Luna?

Requests submitted through the asynchronous batch endpoint are billed at 50% off both input and output rates, bringing input to $0.050 and output to $0.250 per million tokens.

What is GPT-6 Luna's context window?

1.1M tokens of context with up to 128K output tokens per request. A larger context window raises the ceiling on what you can send, not the price per token, but filling it on every request is one of the most common causes of an unexpected bill.

Running GPT-6 Luna in production?

Finitizer Tokenomics reads what this model actually costs you from your own bills and exports, shows which workload, team or API key is spending it, flags a spike or a new spend source the day your data shows it, and forecasts where the month will land.

See how Finitizer works