GPT-6 Sol vs Luna: benchmarks, pricing and which to use in BrainBox

GPT-6 Sol and GPT-6 Luna have been selectable in the BrainBox Assistant since September 22, 2026, the day OpenAI released them. Both have a 1,050,000 token context window, 128,000 max output tokens and accept images. Sol sits in the Pro category of the picker and Luna in Default.

What are GPT-6 Sol and GPT-6 Luna?

They are the two tiers OpenAI added to the GPT-6 family after Astra. According to the announcement, they were trained "with similar methods as GPT-6 Astra", bringing its advances in professional work, factuality, coding, computer use and alignment "to faster, more affordable models". OpenAI states in the same text that Astra remains its best model across the board, and Astra is not in the BrainBox picker.

The specifications come from the official model pages for GPT-6 Sol and GPT-6 Luna.

What do the benchmarks say?

Artificial Analysis, which measures models on its own, gives GPT-6 Sol 48 points on its Intelligence Index and Luna 37. According to the leaderboard, Sol sits above Grok 4.7 and MiMo V2.6 Pro at 46, and below GPT-6 Astra and Claude Fable 5.1 at 53 and Claude Opus 5.5 at 58. Luna, at 37, is the highest score in its price range.

The benchmarks OpenAI publishes compare cost per task ahead of top score:

The best score in each row is in bold.

The competitor numbers are reported by OpenAI from public reports, not by each lab, and OpenAI notes it used Claude Fable 5 scores where Fable 5.1 scores were unavailable. On AutomationBench it also flags that the Fable 5.1 datapoint understates its cost because it omits the Opus 5 fallbacks, which happened on about 40% of tasks.

Two improvements from the announcement matter more in document work than in the table. On OpenAI's internal factuality evaluation, built from real conversations where users flagged mistakes, Sol makes "about half as many mistakes as its predecessor". And the style changed: OpenAI promises "more clarity, less jargon, fewer odd turns of phrase, fewer low-value details, and slightly shorter answers overall without losing substance".

How does the BrainBox Assistant work with these models?

The BrainBox Assistant is an agent. You choose which Boxes and files it may use and which model does the reasoning; the agent decides the steps. Each one shows in the chat: "Listing sources", "Searching documents", "Reading document" with the pages it opened, "Saving note" when it sets something aside for later, and at the end the answer with page citations.

With a million tokens of context, either tier holds many reads in one conversation before the agent has to compress what it read into notes. The difference is how far the reasoning goes between steps, and there Sol is ahead.

1. Open the Assistant and choose the sources

   In the sidebar you tick the Boxes and files the agent may use. You can also point at a file with @ inside the message.

2. Click the model picker

   It sits in the bottom bar of the chat. A searchable list opens.

3. Type 'GPT-6'

   GPT-6 Sol appears in the Pro category and GPT-6 Luna in Default, with their context and the Images badge.

4. Pick the tier for the task

   Sol for long reviews and complex reasoning; Luna for frequent questions, summaries and batches.

5. Ask for the task

   Page citations, the tools and the agent's visible steps work the same on both tiers.

Select model

Select model

GPT-6

• 

  GPT-6 SolOpenAI

  Flagship tier for complex coding and agentic workflows

  1.05M contextProImages
• 

  GPT-6 LunaOpenAI

  The most efficient GPT-6 tier for high-volume work

  1.05M contextImages

BrainBox is an AI workspace for documents that answers with citations to the exact page. The model changes how the answer is reasoned; the trail back to the source does not.

How many intelligence units does each task use?

BrainBox does not measure usage in tokens but in intelligence units, and each task uses a different number depending on how many searches and reads the agent makes, how much the model reasons and how much it writes. Estimates for the standard plan:

These are estimates: a longer answer, more sources or more agent steps push the number up. For reference, the Elite plan includes 400 units a month. The gap between the two tiers is why Luna is worth keeping as the everyday default: for most questions the answer is the same and the usage is a fraction.

What happens if the Box is larger than the context window?

Nothing is left out. The Assistant does not load the whole Box into the model: it searches the selected sources and reads the pages that answer the question, each with its file and page. It works the same for a Box of 200 pages or 20,000. The model decides how to reason over what it reads; the size of the Box does not decide which model you can pick.

When does Sol make sense, when Luna, and when neither?

For legal teams, the workspace model policy lets you enable Sol for the team or keep Luna only, without touching each account. Citations still point to the page with either tier, so verifying the answer works the same.

How is this different from using GPT-6 in ChatGPT?

ChatGPT Work and Codex give access to the same models, according to OpenAI. What differs is everything around them.

Artificial Analysis measures Sol at about 115 tokens per second and Luna at about 154 once they start writing, with over a minute of thinking before the first token at max effort. In the Assistant that shows up as a long task advancing step by step over several minutes.

Sources

• OpenAI, Introducing GPT-6 Sol and Luna: announcement of September 22, 2026, benchmarks, factuality, style and availability.
• OpenAI, model pages for GPT-6 Sol and GPT-6 Luna: context, max output, modalities, effort levels and knowledge cutoff.
• Artificial Analysis, model pages for GPT-6 Sol and GPT-6 Luna: Intelligence Index, speed and verbosity.
• Artificial Analysis, model leaderboard: scores for Claude Opus 5.5, GPT-6 Astra, Claude Fable 5.1, Grok 4.7 and MiMo V2.6 Pro.