Sold by: OpenAI
Deployed on AWS
AWS Free Tier
OpenAI GPT-6 Luna is the most efficient model from OpenAI for focused, high-volume tasks.
Overview
OpenAI GPT-6 Luna is the most efficient model from OpenAI for focused, high-volume tasks. It brings GPT-6 intelligence to repeatable work with a clear goal, giving developers a practical way to serve many users or process large volumes of documents and requests.
Luna is well suited for summarizing documents, extracting key information, and powering assistants that answer focused questions using business data returned by application tools. It improves on GPT-5.6 Luna in factual reliability, communication, and selected coding and workflow evaluations. Developers can tune reasoning effort to balance the quality, speed, and cost their workload requires.
Through Amazon Bedrock, organizations can use GPT-6 Luna in the AWS environment where their applications and workflows already run, alongside the AWS security, governance, procurement, and billing processes they already use.
Highlights
- Scale focused, repeatable tasks such as document summarization, information extraction, and question answering grounded in business data.
- Bring improved factual reliability and clearer communication to everyday applications, with adjustable reasoning effort to balance quality, speed, and cost.
- Access GPT-6 Luna through Amazon Bedrock to bring the most efficient model from OpenAI to high-volume applications in your existing AWS environment.
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
input_tokens_global_standard | $0.10 |
input_tokens_global_priority | $0.20 |
input_tokens_global_flex | $0.05 |
output_tokens_global_standard | $0.50 |
output_tokens_global_priority | $1.00 |
output_tokens_global_flex | $0.25 |
cache_read_tokens_global_standard | $0.01 |
cache_read_tokens_global_priority | $0.02 |
cache_read_tokens_global_flex | $0.005 |
cache_write_tokens_30m_global_standard | $0.125 |
Dimensions summary
You pay only for what you use, measured per token. Charges split by token role: input, output, cache reads, and 30-minute cache writes. Each role is priced separately, so writing to cache costs differently than reading from it. Three service modes affect rate: Standard, Priority, and Flex. Long-context dimensions apply when your requests use extended context windows. A parallel set of global dimensions covers global routing. Not every combination exists—Priority applies to short-context roles only, while Flex and Standard extend across long-context roles. Total cost depends on token volume, role, mode, and context length.
Top-of-mind questions for buyers
Each unit is one token, a small piece of text the model processes. Input tokens cover text you send. Output tokens cover text the model returns. Cache read and cache write tokens meter reuse of stored context. You are charged per token consumed in each role.
Each token role bills independently and adds together. A single request can generate input, output, cache read, and cache write charges at the same time. Output tokens usually cost more per token than input. Long-context requests shift charges to the long-context dimensions. Your total sums every role, mode, and context type used.
The three modes set the per-token rate for the same work. Faster processing carries a higher rate than standard handling; lower-cost handling trades speed for price. Priority applies to short-context roles only. Flex and Standard extend across long-context roles. You select the mode that fits each request's speed needs.
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Delivery details
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