benchrStat hero shows the flagship (Sol), whose price didn't move. Terra and Luna's new prices, context windows, and API IDs are all in the table below.
The full price and spec table
| Model | Input | Output | Cached input | Long-context input/output | Context | Max output | API model ID |
|---|---|---|---|---|---|---|---|
| Sol (flagship) | $5.00 | $30.00 | $0.50 | $10.00 / $45.00 | 1,050,000 | 128,000 | gpt-5.6-sol |
| Terra (balanced) | $2.00 | $12.00 | $0.20 | $4.00 / $18.00 | 1,050,000 | 128,000 | gpt-5.6-terra |
| Luna (cheapest) | $0.20 | $1.20 | $0.02 | $0.40 / $1.80 | 1,050,000 | 128,000 | gpt-5.6-luna |
These are the current rates on OpenAI's API pricing page. Terra and Luna dropped on July 30, 2026 — Terra 20% (from $2.50/$15) and Luna 80% (from $1/$6). Sol's price and the 1.05M context / 128K max output specs for all three tiers are unchanged.
Compare each tier with its nearest alternative
The cleanest way to sanity-check GPT-5.6's prices is to line each model up against an existing OpenAI model at a price you can verify on the live pricing page.
Sol = the GPT-5.5 sticker. Sol's $5/$30 is identical to GPT-5.5 at $5/$30 and didn't move in the July 30 cut. So the flagship of the new series still carries no headline price increase over the current flagship — you'd be paying the same per token for whatever capability gain Sol delivers. For external reference at that tier, Claude Opus 4.8 is $5/$25 (cheaper output) and Gemini 3.1 Pro is $2/$12 (cheaper on both sides).
Terra now undercuts the GPT-5.4 sticker. Terra used to match GPT-5.4's $2.50/$15 exactly; after the cut it's $2/$12, cheaper than GPT-5.4 on both input and output. OpenAI still frames Terra as GPT-5.5-class capability, so the pitch got stronger: GPT-5.5-grade output below the GPT-5.4 price, not just at it.
Luna now undercuts GPT-5 Mini. Luna used to sit between GPT-5 ($1.25/$10) and GPT-5 Mini ($0.25/$2). After an 80% cut, Luna's $0.20 input is now below GPT-5 Mini's $0.25, though its $1.20 output still sits below Mini's $2.00 — Luna wins on both sides now. For an external floor, DeepSeek V4-Pro is $0.435/$0.87: Luna's new input rate beats it, but DeepSeek still wins on output.
The caching and long-context policy
Current cached-input rates are $0.50/$0.20/$0.02 for Sol/Terra/Luna. Long-context pricing (above the short-context threshold) is $10/$45 for Sol, $4/$18 for Terra, and $0.40/$1.80 for Luna. OpenAI's pricing page did not restate batch, flex, or priority rates after the July 30 cut, so treat those older multiples as unconfirmed until OpenAI republishes them. The practical budgeting point is unchanged: output dominates heavy agent workloads.
Cost scenarios
Take a steady agent at 30M input + 10M output per month. On Sol that is $150 + $300 = $450/month; with a 90% cache hit on input it falls to about $15 + $300 = $315/month. The same volume on Terra is now $60 + $120 = $180/month (was $225), and on Luna $6 + $12 = $18/month (was $90) — a fifth of its pre-cut cost.
Use-case fit
Consider for: teams already standardized on the OpenAI stack. Terra now beats the GPT-5.4 rate outright while pairing it with provider-reported SWE-bench Verified (85.2%) and GPQA Diamond (88.0%) scores; Luna is the tier to reconsider if you dismissed it before the cut; and Sol still has the line's 1,050,000-token context maximum. Test the selected tier on your own latency, quality, and cost targets.
Skip if: you are already happy on GPT-5.5 at the same $5/$30 sticker and do not need Sol's benchmark gains or newer tool/reasoning behavior. There is no price-only reason to migrate from GPT-5.5 to Sol — that comparison didn't change.
Decision checklist
The July 30 cut is official and live on OpenAI's pricing page, not a preview announcement. If you budgeted for the old Terra/Luna rates, redo the math — Luna in particular is a fifth of its old cost per token.
Terra's "GPT-5.5-class" claim has the same benchmark numbers behind it as before — SWE-bench Verified 85.2% and GPQA Diamond 88.0%, from OpenAI's system card — now at a lower price. Benchmark it against your own workloads either way; a price cut doesn't change whether the quality claim holds on your tasks.