GPT-6 Sol vs GPT-6 Astra

Specs side by side

Price per token

Prices exclude taxes and are charged from your prepaid USD balance. Both models work through the same key, in the OpenAI-compatible /v1/chat/completions endpoint. Failed generations cost nothing.

GPT-6 Sol is the sensible default in the GPT-6 family, and GPT-6 Astra is the flagship for the cases Sol cannot handle. Astra costs 5 times more for every token, yet it has the same 1.05M-token context and the same 128K output limit. You pay only for answer quality on the hardest tasks, not for bigger limits.

Key differences

• Price. GPT-6 Sol costs $2.16 / $10.80 per 1M tokens, GPT-6 Astra costs $10.80 / $54.00 per 1M tokens. Astra is 5 times more on input, output and cached input. Both have a cached rate ten times below their own input rate.
• Positioning. OpenAI calls Astra its best model across the board and lists software engineering, computer use, browsing, cybersecurity, science and professional work. Sol is for hard tasks you want to iterate on many times without flagship rates.
• Release. Astra came first, on September 3, 2026. Sol and Luna followed on September 22, trained, according to OpenAI, with methods similar to Astra's.
• Parameters. Per OpenAI's API changelog, Astra does not accept custom temperature or top_p values. Strip them when porting older code.
• Shared. 1,050,000-token context, up to 128K output tokens, thinking tokens billed as output, the OpenAI-compatible /v1/chat/completions. Switching is just the model field.

When to pick GPT-6 Sol

• The default for code, tool-calling agents and long-document analysis.
• Tasks run hundreds of times a day, where a 5x rate would eat the budget.
• Iteration: prototype, fix, try again.
• Moving from GPT-5.6 Sol with no code change beyond the model name.

When to pick GPT-6 Astra

• Tasks where Sol gets your test cases wrong and a mistake costs more than the price gap.
• Long end-to-end engineering tasks and architecture reviews.
• Scientific and technical analysis where accuracy matters most.
• A final check on answers produced by cheaper models.

My pattern: most traffic goes to Sol, and only the hard cases reach Astra. For Astra I create a separate API key with a monthly USD limit; once a request would cross it, the API returns 403, so a looping script cannot drain the balance. The whole family, Luna included, is in GPT-6 API pricing.

FAQ

GPT-6 Sol or Astra: which should I use?

Start with Sol. Take 20 to 50 real examples, run them through both, and move to Astra only the task types where Sol clearly loses.

How much more expensive is GPT-6 Astra than Sol?

5 times, on input, output and cached input alike. Current rates: $2.16 / $10.80 per 1M tokens and $10.80 / $54.00 per 1M tokens.

Does Astra have a bigger context window than Sol?

No. Both have 1,050,000 tokens of context and up to 128K output tokens.

How do I keep Astra costs under control?

A separate key with a monthly limit in the dashboard, a short system prompt and a set max_tokens. With long documents, trim what the model does not need, because every input token is billed.

What about GPT-6.1 Sol?

OpenAI released GPT-6.1 Sol on September 29 at the same base price as Sol. The Jantaris catalog serves gpt-6-sol for now; the live list is at GET /v1/models?category=chat.