OpenAI · Model guide

GPT-6 Luna

Q: What is GPT-6 Luna?

GPT-6 Luna is available on CrossModel as openai/gpt-6-luna. It has a 1M-token context window and can return up to 128K tokens per request.

Q: How much does GPT-6 Luna cost?

Currently $ 0.10 per 1M input tokens and $ 0.50 per 1M output tokens. Cached input is billed at $ 0.010 per 1M.

Q: Does GPT-6 Luna support tool calling and structured output?

Tool calling: Supported · Structured output (JSON): Supported · Image input: Supported · Streaming: Supported · Thinking mode: Supported

Q: Which endpoint do I call?

For text models, OpenAI Chat Completions (/v1/chat/completions), OpenAI Responses (/v1/responses) and Anthropic Messages (/v1/messages) all work — pick whichever your SDK already speaks.

Q: Can I try it without writing code?

Yes. Sign in and open the Playground on this page to chat with the model directly — no API key needed. Usage is billed from your wallet at the normal rate.

Compare

openai/gpt-6-lunaReleased Sep 22, 2026

The most efficient GPT-6 model, built for focused, high-volume tasks. It accepts text and images, supports a 1.05M-token context window, and keeps the family's full reasoning effort range.

Modalities

Context

Max output

128K

Price / 1M tokens

$ 0.10in$ 0.50out

StreamingTool callingJSON outputImage inputThinking mode

What this model is good at

What the vendor positions it for, and which of our models to reach for instead.

VendorThe most efficient GPT-6 model for focused, high-volume tasks.source

Best for

High-volume tasks · Serve focused tasks at high request volume.(vendor claim)source
Everyday coding · Handle software-engineering tasks at lower cost per task.(vendor claim)source

Neighbouring models

openai/gpt-6-solstronger —Use Sol when complex coding or agentic workflows need more capability.
openai/gpt-5.6-lunapredecessor —Use GPT-5.6 Luna only for an established compatibility baseline.

Compare them side by side →

Pricing and billing

Tiered pricing: the rate changes once the input passes the threshold.

Price / 1M tokens by input size	Input < 272.0K	Input ≥ 272.0K
Input	$ 0.10	$ 0.20
Output	$ 0.50	$ 0.75
Cache read	$ 0.010	$ 0.020
Cache write	$ 0.13	$ 0.25

Estimate a request

Input tokens10,000

Output tokens2,000

Cache hit rate0%

At this input size you are on the Input < 272.0K tier.

$ 0.0020

Estimated cost per request

10.0K × $ 0.10
+ 2.0K × $ 0.50

≈ $ 2.00 per 1,000 requests

Capabilities and limits

What CrossModel guarantees across every route this model can take right now.

Context window: 1.1M tokens
Max output: 128.0K tokens
Input / output modalities: Text + Image → Text
Streaming: Supported
Tool calling: Supported
Structured output (JSON): Supported
Image input: Supported
Thinking mode: Supported· always on
Reasoning effort: none · low · medium · high · xhigh · max
Available endpoints: /v1/chat/completions · /v1/responses · /v1/messages

First-party sources:Specsdevelopers.openai.com 1 developers.openai.com 2Capabilitiesdevelopers.openai.com 1 developers.openai.com 2

Published benchmarks

Scores the vendor reported, with the evaluation setup each one came from.

Coding

DeepSWE 1.1
resolved_rate·OpenAI · 2026-09-22effort maxsetup not fully disclosed
发布页正文给出的单一推理档位成绩；研究/API 配置可能不同于生产。
66.6%

Vendor-reported numbers, not CrossModel measurements. Scores are only comparable when the benchmark version, metric and evaluation setup match, so nothing here is averaged or ranked.

Use it in your tools

Point the base URL at CrossModel and paste this model ID — every tool below has a setup guide.

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Frequently asked questions

What is GPT-6 Luna?

GPT-6 Luna is available on CrossModel as openai/gpt-6-luna. It has a 1M-token context window and can return up to 128K tokens per request.

How much does GPT-6 Luna cost?

Currently $ 0.10 per 1M input tokens and $ 0.50 per 1M output tokens. Cached input is billed at $ 0.010 per 1M.

Does GPT-6 Luna support tool calling and structured output?

Tool calling: Supported · Structured output (JSON): Supported · Image input: Supported · Streaming: Supported · Thinking mode: Supported

Which endpoint do I call?

For text models, OpenAI Chat Completions (/v1/chat/completions), OpenAI Responses (/v1/responses) and Anthropic Messages (/v1/messages) all work — pick whichever your SDK already speaks.

Can I try it without writing code?