Tasks and inputs
GPT-6 Luna is listed for Image-text-to-text, Text generation. It accepts text, image and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
GPT-6 Luna is OpenAI's lower-cost GPT-6 option for text and image tasks that return text.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
GPT-6 Luna is OpenAI's lower-cost GPT-6 option for text and image tasks that return text.
Luna is worth testing for frequent, bounded work such as classifying a request, extracting fields or drafting a short response. Build a test set with ambiguous inputs and cases where the correct answer is to leave a field unknown. The important measure is the share of outputs your application can accept without repair.
The Responses API provides tool workflows. Chat Completions function calling requires reasoning_effort set to none. Reasoning effort affects both response time and the amount of generated work, so keep it fixed when measuring an alternative.
The documented context allowance is 1,050,000 tokens, with up to 128,000 output tokens. Standard rates for prompts up to 272,000 input tokens are $0.1 input and $0.5 output per million tokens. Longer prompts use higher rates across the request; cache writes, processing tiers and regional options can also change the bill.
Keep representative tasks, expected outcomes and failure cases together. Measure total cost to an accepted result, time to completion and the work a person must redo. Compare a smaller route before assigning every request to the same model. Explore OpenAI models or compare two candidates.
Compare the model on the work you need to complete.
GPT-6 Luna is listed for Image-text-to-text, Text generation. It accepts text, image and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 1.05M context and 128K maximum output. The listed route charges $0.10 input and $0.50 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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OpenAI
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MiniMax
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