Pick GPT-6 Astra for the hardest, highest-stakes work, GPT-6.1 Sol for most serious everyday work, and GPT-6 Luna for fast, cheap, high-volume tasks. In the GPT-6 Sol vs Astra choice, Sol gets close to Astra at one fifth of the application programming interface (API) price, so start with Sol and move up only when it falls short.
That’s the short version. The rest of this guide covers what each tier is built for, what it costs in the API, where you can use it in ChatGPT, and a simple way to decide. All prices and plan details come from OpenAI’s own pages, checked on November 2, 2026.
What are GPT-6 Astra, Sol, and Luna?
They are three sizes of the same model family, released over about four weeks in fall 2026. Think of them as good, better, and best, with very different price tags.
- GPT-6 Astra launched on September 3, 2026. OpenAI calls it its “most intelligent and aligned model” in the Astra announcement, with top scores in computer use, coding, cybersecurity, and science.
- GPT-6 Sol and GPT-6 Luna followed on September 22. OpenAI’s Sol and Luna announcement says they were trained with methods similar to Astra’s, and that their API prices are 50% lower than the GPT-5.6 promotional rates.
- GPT-6.1 Sol arrived on September 29, during DevDay. OpenAI’s GPT-6.1 Sol post describes it as an upgrade to GPT-6 Sol with “near-Astra” intelligence at one fifth of Astra’s price.
In the API, GPT-6.1 Sol is now the Sol to use. The original GPT-6 Sol is still listed at the same input and output price, but its cached input costs twice as much.
There’s also a fourth name you may see. On October 26, OpenAI added GPT-6.1 Terra, which sits between Sol and Luna at $1 per million input tokens and $5 per million output tokens. It’s useful to know it exists, but this guide sticks to the three main tiers. For the wider picture of everything that shipped this season, see our roundup of fall 2026 AI model releases.
How much does each GPT-6 model cost?
Here are OpenAI’s standard API prices per million tokens, from the OpenAI API pricing page as of November 2, 2026.
| Model | Input | Cached input | Output | Best for |
|---|---|---|---|---|
| GPT-6 Astra | $10.00 | $1.00 | $50.00 | The hardest, highest-stakes tasks |
| GPT-6.1 Sol | $2.00 | $0.10 | $10.00 | Serious everyday work and agents |
| GPT-6 Luna | $0.10 | $0.01 | $0.50 | High-volume, narrow tasks |
The gap is large. Astra costs 5 times as much as Sol and 100 times as much as Luna, per token. A job that costs $50 on Astra would cost about $10 on Sol and about $0.50 on Luna, if each model used the same number of tokens.
A few pricing details matter in practice:
- Long prompts cost more. Above 272,000 input tokens, input and cached input prices double, and output prices rise by half.
- Batch and Flex processing cost about half the standard rate, if you can wait for results.
- Fast mode (formerly called Priority) costs twice the standard rate.
- Cheap per token isn’t always cheap per task. A model that needs more attempts, or more reasoning tokens, can cost more overall.
If you want to compare these prices with Claude, Gemini, and other providers, our AI API pricing comparison lays them side by side.
What is GPT-6 Astra best at?
Astra is the model to use when a wrong answer is expensive. OpenAI positions it for complex reasoning, coding, computer use, research, and polished documents, slides, and spreadsheets.
OpenAI’s launch post reports, for example, that Astra scored 57.9% on Terminal-Bench 4.0, a test of complex terminal tasks, compared with 55.8% for Claude Fable 5.1 and 37.3% for GPT-5.6 Sol. Those are OpenAI’s own numbers, so treat them as a guide, not a verdict.
According to its model page, Astra has a 1,050,000-token context window (up to 922,000 tokens of input) and can write up to 128,000 tokens in one reply. It supports five reasoning effort levels, from low to max, but not “none,” so it always thinks before answering.
Good fits for Astra:
- Long, multistep agent tasks where a mistake halfway through wastes hours
- Hard debugging in a large codebase
- Legal, financial, or scientific analysis that someone will act on
- Final drafts of important documents, decks, and models
Is GPT-6.1 Sol good enough instead of Astra?
For most people, yes. That’s the whole point of the GPT-6 Sol vs Astra trade-off: Sol gives up a little capability to save a lot of money.
OpenAI’s GPT-6.1 Sol post gives a few data points. On the OSWorld 2.0 computer-use test, at maximum reasoning effort, GPT-6.1 Sol came within 2.1 points of Astra at about one seventh of the cost per task. On a document-reading benchmark called GDP.pdf, OpenAI says it approached Astra’s score at about one fifth of the cost. OpenAI also says the share of answers with factual errors on hard prompts fell from 11.4% to 7.7% compared with GPT-6 Sol, at low reasoning effort.
Sol has the same 1,050,000-token context window and 128,000-token output limit as Astra. It supports reasoning effort from low to max, with medium as the default.
Choose Sol when:
- You’re building an agent or app that runs many times a day
- You want strong coding and document work without Astra’s bill
- You plan to iterate a lot, so cost per attempt matters
- You’ve tested Sol on your own tasks and the quality holds
When should you use GPT-6 Luna?
Use Luna when the task is clear, narrow, and repeated thousands of times. OpenAI calls it its “most efficient model for focused, high-volume tasks.”
Luna is the only one of the three that supports a “none” reasoning setting, so it can answer instantly without thinking first. It can also reason at higher effort levels when you need it to. In OpenAI’s Sol and Luna announcement, Luna at max effort scored 66.6% on the DeepSWE v1.1 coding test, which OpenAI says was on par with Claude Opus 5 at medium effort.
Typical Luna jobs:
- Classifying or tagging support tickets, reviews, or emails
- Pulling fields out of forms, invoices, or receipts
- Routing requests to the right model or team
- Short summaries and rewrites at scale
- Simple chatbot replies where speed matters more than depth
Which GPT-6 model can you use in ChatGPT?
This part is confusing, because ChatGPT doesn’t show the tier names the way the API does. Here’s what OpenAI’s Help Center article on GPT-6 and other models in ChatGPT says, as of November 2, 2026.
In ChatGPT’s main Chat, you pick GPT-6 and then a thinking level with a slider. GPT-6 Sol powers the Instant, Medium, High, and Extra High levels. The Pro level uses GPT-6 Pro, powered by GPT-6 Astra.
| Plan | GPT-6 in Chat | Astra access |
|---|---|---|
| Free and Go | No; Chat uses GPT-5.6 Luna | No |
| Plus | Medium and High levels | In ChatGPT Work and Codex only |
| Pro ($100 and $200) | All levels, including Pro | In Chat (as GPT-6 Pro), Work, and Codex |
| Business and Enterprise | All levels, including Pro | GPT-6 Pro in Chat; Enterprise depends on admin settings |
A few extra notes from OpenAI’s pages:
- GPT-6.1 Sol is a separate model option in ChatGPT Work and Codex, not in regular Chat.
- GPT-6 Luna, per the September 22 announcement, was made available to Free and Go users in the desktop app, while the Help Center says regular Chat on those plans runs GPT-5.6 Luna.
- GPT-6 Pro has usage limits, even on Pro plans.
Because the rollout is still moving, check the model menu in your own account before you pay for an upgrade.
Is GPT-6.2 Astra out?
No. OpenAI has not announced a GPT-6.2 Astra. There have been reports of one. On November 1, 2026, PANews reported that some Codex users saw a “gpt-6.2-astra” label in their usage details, which led to speculation about a quiet test.
Those reports rest on screenshots that haven’t been independently verified, and OpenAI hadn’t commented when they were published. Until OpenAI announces it, treat GPT-6.2 Astra as a rumor and plan around the models you can actually use today.
How do you choose between Astra, Sol, and Luna?
Use this four-step test. It works for API projects and for deciding what to select in ChatGPT.
- Start with GPT-6.1 Sol. It’s the default sensible choice for real work.
- Drop to Luna if the task is simple and repeated, and Luna’s answers pass a spot check of 20 to 50 examples.
- Move up to Astra only where Sol makes mistakes that matter, such as long agent runs, hard code, or high-stakes analysis.
- Mix them. Many teams use Luna to sort requests, Sol to do most of the work, and Astra for the final check or the hardest cases.
Quick guide by use case:
| If you need to… | Pick |
|---|---|
| Tag 100,000 support tickets | Luna |
| Build a coding agent you run all day | GPT-6.1 Sol |
| Draft a client-ready financial model | Astra |
| Summarize meeting notes | Luna or Sol |
| Fix a bug nobody on the team can find | Astra |
| Power a customer-facing chatbot | Sol, with Luna for simple replies |
Our general guide on how to choose an AI model walks through testing models on your own tasks, which beats any benchmark.
How does GPT-6 compare with Claude?
The tiers line up neatly with Anthropic’s lineup. GPT-6 Astra’s $10 input and $50 output price matches Claude Fable 5.1’s list price, and GPT-6.1 Sol’s $2 and $10 matches Claude Sonnet 5.5, according to Anthropic’s models overview as of November 2, 2026. Claude Opus 5.5 sits between them at $4 and $20.
Matching prices don’t mean matching results, so test both on your own work. If you’re weighing Anthropic’s options, our comparison of Claude Opus 5.5 vs Sonnet 5.5 covers that decision, and you can browse all our coverage of AI models for more.
FAQ
What is the difference between GPT-6 Sol and GPT-6.1 Sol?
GPT-6.1 Sol is an upgrade to GPT-6 Sol, released on September 29, 2026. OpenAI says it is much stronger at coding, document understanding, and multistep workflows. Both cost $2 per million input tokens and $10 per million output tokens in the API, but GPT-6.1 Sol’s cached input costs $0.10, half of GPT-6 Sol’s $0.20. In ChatGPT, GPT-6 Sol powers Chat, while GPT-6.1 Sol is offered in Work and Codex.
Is GPT-6 Astra available on ChatGPT Plus?
Partly. According to OpenAI’s Help Center as of November 2, 2026, Plus includes GPT-6 Astra in ChatGPT Work and Codex, with usage limits. In regular Chat, Plus users get GPT-6 at the Medium and High thinking levels, which run on GPT-6 Sol. The Pro level, powered by Astra, is reserved for Pro, Business, and Enterprise plans.
Do all three GPT-6 models have the same context window?
Yes. OpenAI’s model pages list a 1,050,000-token context window for GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna, with a maximum input of 922,000 tokens and up to 128,000 output tokens. Keep in mind that prompts over 272,000 input tokens are billed at higher long-context rates, and very long prompts can still reduce answer quality.
Is GPT-6 Luna free to use?
Not in the API, where it costs $0.10 per million input tokens and $0.50 per million output tokens as of November 2026. OpenAI’s September 22 announcement said Free and Go users could use GPT-6 Luna in the ChatGPT desktop app. OpenAI’s Help Center says the regular Chat model on Free and Go is GPT-5.6 Luna, so availability depends on where you use it.
Which GPT-6 model is best for coding?
For the hardest coding tasks, OpenAI positions GPT-6 Astra as its best model. For everyday coding agents, GPT-6.1 Sol is the practical pick, since OpenAI reports it reaches near-Astra results at about one fifth of the price. GPT-6 Luna works for quick, well-defined coding tasks at scale. Test each on your own codebase before committing.
Will there be a GPT-6.2?
OpenAI hasn’t announced one. In early November 2026, some users reported seeing a “gpt-6.2-astra” label in Codex usage data, but those screenshots are unverified and OpenAI hasn’t confirmed anything. Until there’s an official announcement, plan your work around GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna, which are available today.
