Model comparison
GPT-6.1 Sol vs GPT-6 Luna: which is cheaper, and which should you use?
GPT-6 Luna is cheaper: a support chatbot handling 1,000 requests a day costs about $8.59 a month on it against $169.57 on GPT-6.1 Sol (20×). GPT-6.1 Sol lists $2 input and $10 output per million tokens; GPT-6 Luna lists $0.10 and $0.50. Context: 1,050,000 vs 1,050,000 tokens. Prices checked 2026-10-16.
Sol is OpenAI’s main model and Luna its small, low-cost tier. They share the same API and long-prompt rules, so the choice is whether Luna is good enough for your high-volume work.
- Input / 1M
- $2
- Output / 1M
- $10
- Context
- 1,050,000
- Max output
- 128,000
- Input / 1M
- $0.10
- Output / 1M
- $0.50
- Context
- 1,050,000
- Max output
- 128,000
Verdict
Which should you pick, GPT-6.1 Sol or GPT-6 Luna?
GPT-6 Luna has the lower list prices: 20× cheaper per input token and 20× per output token. On our data, GPT-6 Luna has the edge for the lowest bill, very long prompts, repeated prompts and batch jobs, and GPT-6.1 Sol has no measurable edge; its case rests on answer quality, so choose it only if it does clearly better in your own tests. For scale, a support chatbot handling 1,000 requests a day costs about $169.57 a month on GPT-6.1 Sol and $8.59 on GPT-6 Luna.
- Lowest bill for typical workloadsPick GPT-6 Luna
- GPT-6 Luna costs less on all 4 workloads below, 18× to 20× cheaper than GPT-6.1 Sol at list prices.
- Very long prompts (whole codebases, long documents)Pick GPT-6 Luna
- Both read about 1,050,000 tokens per request. One 840,000-token prompt with a 2,000-token reply costs $3.39 on GPT-6.1 Sol and $0.17 on GPT-6 Luna. GPT-6.1 Sol charges $4 / $15 per 1M once a prompt passes 272,000 tokens. GPT-6 Luna charges $0.20 / $0.75 per 1M once a prompt passes 272,000 tokens.
- Long replies (reports, large code files)Either
- Both cap a single reply at about 128,000 tokens.
- Images, audio, video or files in the promptEither
- Both accept images and files as well as text.
- Repeated long prompts (prompt caching)Pick GPT-6 Luna
- GPT-6 Luna bills cached input at $0.01 per 1M (10% of its input price), against $0.10 per 1M (5% of its input price) for GPT-6.1 Sol.
- Overnight batch jobsPick GPT-6 Luna
- Both offer batch prices; on the document summariser workload GPT-6 Luna costs $5.02 a month against $100.38.
- Self-hosting or choosing your own hostEither
- Neither has downloadable weights: both are only available through their provider’s API and cloud partners.
Criteria use only list prices, published limits and the features each provider declares. We don’t rank answer quality; test both models on your own prompts before you commit.
Specs
How do GPT-6.1 Sol and GPT-6 Luna compare on specs?
| Spec | GPT-6.1 Sol | GPT-6 Luna |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input / 1M tokens | $2 | $0.10 (better) |
| Output / 1M tokens | $10 | $0.50 (better) |
| Cached input / 1M | $0.10 | $0.01 (better) |
| Cache write / 1M | $2.50 | $0.125 |
| Batch in / out | $1 / $5 | $0.05 / $0.25 (better) |
| Long-prompt price | $4 / $15 over 272,000 | $0.20 / $0.75 over 272,000 |
| Context window | 1,050,000 | 1,050,000 |
| Max output | 128,000 | 128,000 |
| Accepts | text, images, files | text, images, files |
| Image input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning mode | Yes | Yes |
| Prompt caching | Yes | Yes |
| Structured output | Yes | Yes |
| Open weights | No | No |
| Knowledge cutoff | Not published | Not published |
| First listed | 2026-09-29 | 2026-09-22 |
Prices in US dollars per million tokens. Highlighted: the lower price or larger limit where the difference is over 5%. Features are as declared by each provider’s API; “First listed” is when our data source first listed the model. Long-prompt prices apply to the whole request once the prompt passes the threshold.
Costs
What do GPT-6.1 Sol and GPT-6 Luna cost for real workloads?
| Workload | Tokens in / out | Requests/day | GPT-6.1 Sol / month | GPT-6 Luna / month | Cheaper |
|---|---|---|---|---|---|
| Support chatbotCalculator: GPT-6.1 Sol · GPT-6 Luna | 1,500 / 400 | 1,000 | $169.5750% cached | $8.5950% cached | GPT-6 Luna (20×) |
| RAG appCalculator: GPT-6.1 Sol · GPT-6 Luna | 6,000 / 500 | 500 | $223.8720% cached | $11.2820% cached | GPT-6 Luna (20×) |
| Coding agentCalculator: GPT-6.1 Sol · GPT-6 Luna | 40,000 / 2,000 | 200 | $238.4780% cached | $12.9080% cached | GPT-6 Luna (18×) |
| Document summariserCalculator: GPT-6.1 Sol · GPT-6 Luna | 8,000 / 600 | 300 | $100.38batch | $5.02batch | GPT-6 Luna (20×) |
Each row uses the same token counts for both models and list prices, with caching and batch discounts only where the provider publishes them. A month is 365 ÷ 12 days. The support chatbot reads 50% of its prompt from the cache. The RAG app reads 20% of its prompt from the cache. The coding agent reads 80% of its prompt from the cache. The document summariser runs as a batch job where a batch price exists. Open either model in the LLM cost calculator to change any number.
Tokenizers
Are their per-token prices comparable?
Not exactly. Each model splits text into tokens its own way, so the same prompt can be a different number of tokens on GPT-6.1 Sol and GPT-6 Luna, and the cheaper per-token price isn’t always the cheaper bill. Where a tokenizer isn’t public or measured we say so rather than guess.
| Model | Tokenizer | Tokens per 1,000 words | Output per 1M words |
|---|---|---|---|
| GPT-6.1 Sol | OpenAI hasn’t published the tokenizer GPT-6.1 Sol uses, so its count for a given text isn’t known exactly. | ||
| GPT-6 Luna | OpenAI hasn’t published the tokenizer GPT-6 Luna uses, so its count for a given text isn’t known exactly. | ||
English prose, measured on the Universal Declaration of Human Rights (2026-10-11) or taken from the provider’s published words-per-token figure. Code, JSON and other languages use more tokens per word. Count your own text in the token counter or convert with tokens to words.
FAQ
GPT-6.1 Sol vs GPT-6 Luna questions
Is GPT-6.1 Sol cheaper than GPT-6 Luna?
GPT-6.1 Sol costs $2 per million input tokens and $10 per million output tokens; GPT-6 Luna costs $0.10 and $0.50. For a support chatbot handling 1,000 requests a day, that is about $169.57 a month on GPT-6.1 Sol against $8.59 on GPT-6 Luna, so GPT-6 Luna is 20× cheaper there. Try your own numbers in the LLM cost calculator.
Which has the bigger context window, GPT-6.1 Sol or GPT-6 Luna?
Their context windows are about the same size. GPT-6.1 Sol reads up to 1,050,000 tokens (roughly 787,500 English words) and writes up to 128,000 tokens per reply. GPT-6 Luna reads up to 1,050,000 tokens (roughly 787,500 English words) and writes up to 128,000 tokens per reply. The window is shared between your prompt and the reply. Word counts use a rough 0.75 words per token; real ratios depend on the tokenizer.
Is GPT-6.1 Sol better than GPT-6 Luna?
We don’t score answer quality, so no page of ours can honestly say one is better overall. On what we can measure, GPT-6 Luna has the edge for the lowest bill, very long prompts and repeated prompts. Run both on a sample of your own prompts and compare the answers and the bill before you choose.
Is GPT-6.1 Sol or GPT-6 Luna better for coding?
We don’t publish benchmark scores, so this page can’t say which writes better code. What we can show is cost: a coding agent re-sending 40,000 tokens of context (80% cached) and writing 2,000 tokens, 200 times a day, costs about $238.47 a month on GPT-6.1 Sol and $12.90 on GPT-6 Luna. Both support tool calling. Test both on tasks from your own repository.
Can I switch from GPT-6.1 Sol to GPT-6 Luna without rewriting my code?
Usually, yes. Both are on OpenAI’s API, so switching is a change of model ID (openai/gpt-6.1-sol to openai/gpt-6-luna on OpenRouter) plus a re-test of your prompts. Check that the features you use, such as caching or tool calling, are listed for both.
Are GPT-6.1 Sol and GPT-6 Luna open source?
No. Neither GPT-6.1 Sol nor GPT-6 Luna has published weights: you can only use them through OpenAI’s API and their cloud partners. If you need a model you can host yourself, compare open-weight options in the model comparison table.
Do GPT-6.1 Sol and GPT-6 Luna count tokens the same way?
Not necessarily. Each model splits text into tokens with its own tokenizer, so the same prompt can be a different number of tokens on each, and per-token prices aren’t directly comparable. OpenAI hasn’t published the tokenizer GPT-6.1 Sol uses, so its count for a given text isn’t known exactly. OpenAI hasn’t published the tokenizer GPT-6 Luna uses, so its count for a given text isn’t known exactly. Count your own text with the token counter or convert with tokens to words.