GPT-6 Luna
- Input / 1M tokens
- $0.10
- Output / 1M tokens
- $0.50
API models · Side by side
GPT-6 Luna vs GPT-6 Sol
Compare two GPT-6 API options before budgeting for a chat, writing or automation workflow. Start with the price difference, then check the inputs and limits your application needs.
GPT-6 Sol
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $10.00
The short answer
- Both listings accept text, images and files and return text.
- Luna has lower listed base token prices. That is a cost difference, not evidence of equal answer quality.
- Both use higher token rates for long prompts. Include reasoning and tool usage when estimating the full bill.
Compare the details
Compare context, supported inputs and usage costs. Highlighted rows show a difference.
| Feature | GPT-6 Luna | GPT-6 Sol |
|---|---|---|
| Input formats | file, image, text | file, image, text |
| Output formats | text | text |
| Context / position limit | 1,050,000 | 1,050,000 |
| Maximum output tokens | 128,000 | 128,000 |
| Developer features | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length |
| Cached input / 1M tokens | $0.01 | $0.20 |
| Cache write / 1M tokens | $0.13 | $2.50 |
| USD input / 1M tokens | $0.10 | $2.00 |
| USD output / 1M tokens | $0.50 | $10.00 |
| Model identifier | openai/gpt-6-luna | openai/gpt-6-sol |
API pricing
Prices are in USD per million tokens. Input is what you send; output is what the model generates. Claude and ChatGPT subscriptions are billed separately.
GPT-6 Luna: long-prompt rates
- Long-prompt threshold: 272,000 prompt tokens. Input: $0.20 / 1M. Output: $0.75 / 1M.
GPT-6 Sol: long-prompt rates
- Long-prompt threshold: 272,000 prompt tokens. Input: $4.00 / 1M. Output: $15.00 / 1M.
Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.
Compare local modelsWhat those prices mean in practice
Each example uses the same token budget for both models. These are calculations, not measured workloads. Cache discounts, media, tools and extra reasoning are excluded.
| Workload | GPT-6 Luna | GPT-6 Sol |
|---|---|---|
| 1,000 short requestsPer request: 2,000 input + 500 output tokens | $0.45 | $9.00 |
| 100 document summariesPer request: 20,000 input + 1,000 output tokens | $0.25 | $5.00 |
| 10 long-document requestsPer request: 300,000 input + 2,000 output tokens | $0.61 | $12.30 |
Estimate = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000. Long-prompt rates are applied where the pricing data provides them. Real requests can use different amounts of output.
Choosing for your project
Start with the formats you need to send, then compare the context allowance and the cost examples. For an existing application, check tool calls and response formats before changing its model. A higher context limit or a lower token price does not, on its own, tell you which answer will be more useful.