GPT-5.6 Terra vs GPT-5.6 Luna
Which one to choose
Pick GPT-5.6 Terra for everyday coding, writing and analysis where you want a capable middle tier. Pick GPT-5.6 Luna for fast, high-volume work such as classification, extraction and routing, where a quick answer matters more than deep reasoning. Both read text and images, call tools and return structured JSON. Terra is the model to step up to when Luna starts failing tasks, and Luna is the one to use when volume is the constraint.
Pricing comparison
| GPT-5.6 Terra | GPT-5.6 Luna | |
|---|---|---|
| Model maker | OpenAI | OpenAI |
| Delivery availability | Available | Available |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 128K |
| Official price | Input$2.00per 1M tokensOutput$12.00per 1M tokens | Input$0.20per 1M tokensOutput$1.20per 1M tokens |
| TokenLab price | Input$0.60per 1M tokensOutput$3.60per 1M tokens | Input$0.06per 1M tokensOutput$0.36per 1M tokens |
| Model performance |
|
|
| Capabilities | CodeJSON modePrompt CacheReasoningTool useVision | CodeJSON modePrompt CacheReasoningTool useVision |
Choose GPT-5.6 Terra when
- Your tasks need real coding or analysis ability, not only quick answers
- Luna's results fall short on multi-step requests
- You want one default for most jobs in the family
Choose GPT-5.6 Luna when
- You process steady, high-volume traffic and need fast replies
- Requests are simple: tagging, extraction, short summaries
- You want a cheap pipeline step that can still take images and call tools
How they differ
| Aspect | GPT-5.6 Terra | GPT-5.6 Luna |
|---|---|---|
| Tier | Balanced middle model of GPT-5.6. | Smallest and most cost-efficient model of GPT-5.6. |
| Task depth | Covers most coding and writing jobs without flagship overhead. | Meant for work that has to be quick rather than deeply reasoned. |
| Failure mode | Handles harder multi-step requests than Luna. | OpenAI's family guidance suggests moving up when tasks keep failing. |
| Reasoning use | Adjustable reasoning serves both quick replies and slower analytical turns. | Adjustable reasoning lets simple turns skip extended thinking. |
| Interface | Text and images in, tool calls and schema-checked JSON out. | Identical request surface, so changing tiers needs no format changes. |
Summary
- GPT-5.6 Terra: Input $0.60 / Output $3.60 per 1M tokens; GPT-5.6 Luna: Input $0.06 / Output $0.36 per 1M tokens. Rates depend on the billing unit, specification, and usage. Compare matching conditions in the model's detailed pricing; a single rate does not determine the total cost.
FAQ
Is GPT-5.6 Terra better than GPT-5.6 Luna?
Terra is the higher tier and does better on harder coding and analysis. Luna is better suited to simple, high-volume tasks where speed and low cost matter more.
Can I switch from Luna to Terra without changing prompts?
Yes in format, since both take text and images and use the same tools and structured output. Prompts written to compensate for Luna's limits may be unnecessary on Terra.
Which is better for classification and extraction?
Luna for most cases, since it is built for fast, high-volume work and reads images and returns structured JSON. Use Terra when the documents are messy or the extraction rules need judgement.
Should I combine them?
Yes. Send routine calls to Luna for fast, low-cost handling, and route the ones that fail validation or need real reasoning up to Terra, which shares the same request format.
Which is cheaper, GPT-5.6 Terra or GPT-5.6 Luna?
GPT-5.6 Terra: Input $0.60 / Output $3.60 per 1M tokens; GPT-5.6 Luna: Input $0.06 / Output $0.36 per 1M tokens. Rates depend on the billing unit, specification, and usage. Compare matching conditions in the model's detailed pricing; a single rate does not determine the total cost.
What are the key differences between GPT-5.6 Terra and GPT-5.6 Luna?
Both models share similar capabilities.
Sources
Reviewed Oct 2, 2026