GPT-6 Astra vs Sol vs Luna: Which GPT-6 Tier Should You Use?

GPT-6 ships as Astra ($10/$50), Sol ($2/$10) and Luna ($0.10/$0.50) with identical context windows. Which tier to use, the 272K-token surcharge trap, and a routing pattern that cuts spend without losing quality.

Published 23 September 2026 by Jake Hissitt, Founder of Stob.AI.

GPT-6 ships in three tiers with a hundredfold price spread between the cheapest and the most expensive.

Astra at $10 in / $50 out, Sol at $2 / $10, and Luna at $0.10 / $0.50.

They share the same 1.05 million token context window, the same 128,000 token output limit and the same reasoning controls.

That makes tier selection the highest-leverage cost decision in an OpenAI-based system.

Here is how to make it.

The three tiers side by side   GPT-6 Astra GPT-6 Sol GPT-6 Luna Input / 1M $10.00 $2.00 $0.10 Output / 1M $50.00 $10.00 $0.50 Cached input / 1M $1.00 $0.20 $0.01 Cache write / 1M $12.50 $2.50 — Above 272K input 2x input and cache, 1.5x output on the whole request $4 in / $15 out $0.20 in / $0.75 out Context 1,050,000 1,050,000 1,050,000 Max output 128,000 128,000 128,000 Best for The hardest reasoning and research Coding, agents, general production Classification, extraction, routing The 272K surcharge is the trap Every tier has a long-prompt rule, and Astra's is the harshest: cross 272,000 input tokens and the entire request bills at double the input and cache rate and 1.5 times the output rate.

Not the excess.

The whole request.

A 300,000-token Astra request costs $6.00 on input alone before a single output token.

The same request on Sol costs $1.20, and on Luna $0.06.

If you routinely load large document sets, the correct fix is usually retrieval, not a bigger context window.