GPT-6.1 Terra vs GPT-6 Luna
GPT-6.1 Terra and GPT-6 Luna are within three points on the Models at Work leaderboard, which we treat as a tie (65 vs 64 out of 100). On independent tests alone, GPT-6.1 Terra is ahead (64 vs 39). GPT-6 Luna is cheaper: 1,000 support replies cost about $0.50 at list price, against $5 on GPT-6.1 Terra, which is 10 times as much. On the Artificial Analysis Intelligence Index, one of the independent tests, GPT-6.1 Terra leads 51 to 28.
| GPT-6.1 Terra · OpenAI | GPT-6 Luna · OpenAI | |
|---|---|---|
| Leaderboard rank | #13 | #14 |
| Score (0–100) | 65 | 64 |
| Kind of work | Everyday default | High-volume work |
| Price per 1M tokens | $1 to read · $5 to write | $0.10 to read · $0.50 to write |
| Reads at once | 1.05M tokens (about 788,000 words) | 1M tokens (about 750,000 words) |
| Where you can get it | OpenAI API, Amazon Bedrock, Microsoft Foundry, Gemini Enterprise Agent Platform (Google Cloud), ChatGPT Plus, Pro, Business, Enterprise and Edu | OpenAI API, Amazon Bedrock, Microsoft Foundry, Gemini Enterprise Agent Platform (Google Cloud) |
| Can a company host it itself | No | No |
| Artificial Analysis Intelligence Index | 51 | 28 |
| Humanity's Last Exam, Diamond (Scale) | 35.70 | Not measured |
| Humanity's Sixth Sense (Scale) | Not measured | 21.00 |
| Best for | High-volume back-office tasks, Filling in forms and moving data between systems, Summarising documents | Simple extraction from forms and emails, Short routine replies, Sorting messages |
Cost of 1,000 jobs
| 1,000 of these | GPT-6.1 Terra | GPT-6 Luna |
|---|---|---|
| Support repliesthe customer message, the account notes and two help articles read; a 300-word reply written | $5 | $0.50 |
| Documents processeda two-page invoice or form read; the fields pulled out | $3.50 | $0.35 |
| Calls summariseda 40-minute call transcript read; a summary and next steps written | $13 | $1.30 |
| Contracts revieweda 40-page contract read against a checklist; a memo of issues written | $38 | $3.75 |
| Drafts writtena brief and one example read; a 600-word email or proposal section written | $5.50 | $0.55 |
Worked out from each vendor’s list price and a fixed size for each job. A product built on a model charges its own price on top. See what every model costs for the same jobs.
Choose GPT-6.1 Terra for
- High-volume back-office tasks
- Filling in forms and moving data between systems
- Summarising documents
Half the list price of GPT-6.1 Sol for four points less on Artificial Analysis's index (51 against 55): the cheaper OpenAI default where the work is routine.
Caveats: Requests that feed it more than 272,000 tokens of text at once are billed at twice the input price and 1.5 times the output price, per OpenAI. The 51 is at its top effort setting, where a test task took 14.1 minutes; at the next setting down it scores 42. OpenAI sells it for operating software on screen like a person would; no independent test of that was found. The ChatGPT plans are listed from our researcher's reading of OpenAI's help page, which blocked automated reading this run.
Choose GPT-6 Luna for
- Simple extraction from forms and emails
- Short routine replies
- Sorting messages
OpenAI's cheapest model, at the same list price as Claude Haiku 5.5 but eight points behind it on Artificial Analysis's index (28 against 36).
Caveats: It ranks 14th largely because price is 30% of the board's score; its test result is low (28 on the index, down from 38 when Artificial Analysis rebuilt it). Users of Haiku 5.5 report it is the noticeably smarter of the two at this price. The release tracker records it as the model behind ChatGPT Free and Go; OpenAI's own page could not be read this run, so ChatGPT is not listed below.
Questions people ask
Which is better, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra and GPT-6 Luna are within three points on the Models at Work leaderboard, which we treat as a tie (65 vs 64 out of 100). On independent tests alone, GPT-6.1 Terra is ahead (64 vs 39). GPT-6 Luna is cheaper: 1,000 support replies cost about $0.50 at list price, against $5 on GPT-6.1 Terra, which is 10 times as much. On the Artificial Analysis Intelligence Index, one of the independent tests, GPT-6.1 Terra leads 51 to 28.
When should I choose GPT-6.1 Terra over GPT-6 Luna?
Choose GPT-6.1 Terra for high-volume back-office tasks, filling in forms and moving data between systems, summarising documents. Half the list price of GPT-6.1 Sol for four points less on Artificial Analysis's index (51 against 55): the cheaper OpenAI default where the work is routine.
When should I choose GPT-6 Luna over GPT-6.1 Terra?
Choose GPT-6 Luna for simple extraction from forms and emails, short routine replies, sorting messages. OpenAI's cheapest model, at the same list price as Claude Haiku 5.5 but eight points behind it on Artificial Analysis's index (28 against 36).
Which is cheaper, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra costs $1 per million tokens it reads (input) and $5 per million tokens it writes (output) on OpenAI's list price (OpenAI API pricing, read Nov 12, 2026). A token is about three-quarters of a word. GPT-6 Luna costs $0.10 per million tokens it reads (input) and $0.50 per million tokens it writes (output) on OpenAI's list price (OpenAI API pricing, read Nov 12, 2026). A token is about three-quarters of a word.
What do 1,000 jobs cost on GPT-6.1 Terra and GPT-6 Luna?
At list price: 1,000 support replies cost $5 on GPT-6.1 Terra and $0.50 on GPT-6 Luna; 1,000 documents processed cost $3.50 on GPT-6.1 Terra and $0.35 on GPT-6 Luna; 1,000 calls summarised cost $13 on GPT-6.1 Terra and $1.30 on GPT-6 Luna; 1,000 contracts reviewed cost $38 on GPT-6.1 Terra and $3.75 on GPT-6 Luna; 1,000 drafts written cost $5.50 on GPT-6.1 Terra and $0.55 on GPT-6 Luna. A product built on either model charges its own price on top.
Scores come from the Models at Work leaderboard: Score is 0 to 100 and computed, not typed. 40% is independent testing (Artificial Analysis, Arena, Scale, Epoch, Vals and others; each test is scaled against the best score on this board, and tests of real work, such as finished freelance projects or professional tasks, count double the exams). 30% is price: the vendor's list price for a typical mix of reading and writing, on a fixed scale from $0.05 to $60 per million tokens, so a model that costs a fifth as much gains real ground. 15% is what people report after running it, from Signals and linked threads. 15% is fit: how much text it can take in at once and where a business can get it (the products and clouds that carry it), with a small credit for open weights. A missing component drops out and the rest are reweighted. A model with no independent test yet is provisional and ranks below every measured one. Within three points is a tie. Vendor-published figures are labelled and never counted. Prices are vendor list prices where published; a typical mix assumes three parts reading to one part writing.