GPT-6 Luna Pro: pricing, context and benchmarks

What you need to know about GPT-6 Luna Pro

OpenAI, based in United States, put GPT-6 Luna Pro online on September 22, 2026. It accepts files, images, and text as input and produces text. Its context window reaches 1,050,000 tokens, larger than 99 % of the models in the registry, and it can write up to 128,000 tokens in one go.

It is a recent model: real-world feedback and independent scores are still scarce.

GPT-6 Luna Pro pricing

On OpenRouter, GPT-6 Luna Pro costs $0.1 per million input tokens and $0.5 per million output tokens. Counting three tokens read for every token written, its average price is $0.2 per million, more expensive than 22 % of paid models (3.8 times cheaper than the median of $0.76).

A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0005. At 1,000 tasks a day, budget $14 a month. The price calculator redoes this with your own volumes.

Tokens already sent and cached are billed at $0.01 per million. With batch processing (delayed answers), the price drops to $0.05 input and $0.25 output.

Performance and benchmarks

Epoch AI does not yet publish a capabilities index for GPT-6 Luna Pro. We therefore show no made-up performance rating: only price, context and features count towards its score.

Features, privacy and local use

• It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
• It can answer in an enforced JSON format (structured outputs).
• It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.

Its weights are not published: it can only be used through the OpenAI API or a broker such as OpenRouter, which means sending your data off your machines.

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