GPT-6 Sol vs GPT-6 Astra

What each one accepts

Token prices

Charged from a prepaid USD balance, no taxes added. One key runs both, through /v1/chat/completions in the OpenAI format. A failed generation is $0.

Treat GPT-6 Sol as the everyday model of the family and GPT-6 Astra as the specialist for cases Sol gets wrong. Astra charges five times more per token, yet its window and output limit are the same as Sol's. What you pay extra for is better answers on the toughest problems, not more room.

When to pick GPT-6 Sol

• You want one go-to model for coding, agents that call functions, and reading long files.
• A task runs hundreds of times a day, so a fivefold rate would swallow the budget.
• You iterate: prototype, fix, try again.
• You are leaving GPT-5.6 Sol and want the upgrade to be a one-word edit.

When to pick GPT-6 Astra

• Sol fails on your test cases, and an error would cost more than the price gap.
• You run long engineering tasks end to end or review a system's architecture.
• Scientific or technical analysis must be as accurate as possible.
• You want a final reviewer for answers from cheaper models.

Differences you will notice

• Rates. GPT-6 Sol is billed at $2.16 / $10.80 per 1M tokens, GPT-6 Astra at $10.80 / $54.00 per 1M tokens. The 5x factor holds on every line of the bill, cached reads included, and each model reads cached input at a tenth of its own input rate.
• Role. OpenAI presents Astra as its strongest model and lists areas such as coding, operating a computer, web research, security, science and office work. Sol is pitched for difficult jobs you rerun often, at a rate well below the flagship.
• Order of release. Astra arrived on September 3, 2026. Nineteen days later, on September 22, OpenAI added Sol and Luna, built with training methods it says resemble Astra's.
• Request fields. OpenAI's API changelog says Astra rejects custom temperature and top_p. Remove them from older code before switching.
• Common ground. A 1,050,000-token window, replies up to 128K tokens, reasoning billed as output, and the same /v1/chat/completions endpoint, so moving between them is one model value.

How to decide

Collect 20 to 50 real examples, run them on both models, then promote to Astra just those kinds of task where Sol is plainly worse. In my own setup the bulk of requests never leaves Sol; Astra sees the rare tough ones. The whole family, with Luna, is broken down in GPT-6 API pricing.

Questions

How do I keep Astra spending in check?

Create a dedicated key for Astra and set a monthly cap on it in the dashboard. Any request that would cross the cap gets a 403, so a runaway script cannot empty your balance. Keeping the system prompt lean and setting max_tokens also helps.

Does Astra read longer documents than Sol?

No. Both stop at 1,050,000 tokens of input and 128K tokens of output. With long files, strip sections that do not matter for the task, since every input token is billed.

Is GPT-6.1 Sol in the catalog?

GPT-6.1 Sol came out on September 29, priced like Sol at base. The catalog currently serves gpt-6-sol; check GET /v1/models?category=chat for the live list.