$10 / $50
GPT-6 Astra, the premium tier: hardest reasoning and the requests where failure is expensive
$2 / $10
GPT-6.1 Sol, the production tier: default for most chat, coding, agentic and generation traffic
$1 / $5
GPT-6.1 Terra, the mid tier: half Sol's rates, the next step up when Luna misses
$0.10 / $0.50
GPT-6 Luna, the volume tier: classification, extraction, short summaries at scale
GPT-6.1 Sol, GPT-6.1 Terra and GPT-6 Luna are OpenAI's three everyday API tiers. Sol is the production model at $2 input / $10 output per million tokens; Terra is the mid tier at $1/$5; Luna, released September 22, 2026, is the volume tier at $0.10/$0.50. GPT-6 Astra sits above all three at $10/$50 for the hardest work.
Should I use GPT-6.1 Sol, Terra or GPT-6 Luna?
It depends on whether the task has a clear success check. GPT-6 Luna, at $0.10 input and $0.50 output per million tokens, suits classification, extraction and short summaries run at volume. GPT-6.1 Sol, at $2/$10, is the default for chat, code, drafting and agent sessions. GPT-6.1 Terra, at $1/$5, is half Sol's price: try it on the traffic Luna gets wrong before you pay for Sol. Send the slice where Sol fails to GPT-6 Astra at $10/$50. The costly mistake is running Sol on work Luna can do: per token it costs 20 times as much.
List prices as of , from OpenAI.
What actually differs between the tiers
Mostly price and how hard a problem each one solves reliably. Sol reasons deeper and costs twenty times Luna per token; Luna is the cheapest and falls over first on hard problems. GPT-6.1 Terra sits in the gap at $1/$5, ten times Luna's rates and half of Sol's, so traffic that misses Luna's bar does not have to jump straight to Sol. Astra is the escalation path for the small slice where Sol is not enough. Check OpenAI's model pages for per-model context and feature limits before you split traffic.
The price math, side by side
| Tier | Input $/M | Output $/M | A code-gen request* | A short extraction* | Anthropic's rung |
|---|---|---|---|---|---|
| GPT-6 Astra | $10.00 | $50.00 | $0.1360 | $0.0148 | Fable 5 ($10/$50, same rates) |
| GPT-6.1 Sol | $2.00 | $10.00 | $0.0272 | $0.0030 | Sonnet 5.5 ($2/$10, same rates) |
| GPT-6.1 Terra | $1.00 | $5.00 | $0.0136 | $0.0015 | Haiku 4.5 ($1/$5, same rates) |
| GPT-6 Luna | $0.10 | $0.50 | $0.0014 | $0.00015 | Haiku 5.5 ($0.10/$0.50 on prompts up to 100K tokens, same rates) |
Table prices as checked November 2, 2026. As of , Anthropic lists Claude Fable 5.1 ($10/$50) and Claude Opus 5.5 ($4/$20) as current models and Fable 5, Opus 5 and Haiku 4.5 as legacy; the quick answer above uses current models.
*List-price math on our measured task token profiles (100/2,700 code-gen, 180/260 extraction); we have not metered these OpenAI models ourselves. We meter Anthropic models directly and publish those bills in the pricing guide. Cached input: $1 on Astra, $0.10 on Sol, $0.05 on Terra, $0.01 on Luna per million tokens. Prices: OpenAI API pricing, Standard short-context rates, verified 2026-11-02.
Which traffic belongs where
Luna: classification, routing decisions, extraction, short summaries, anything you run thousands of times daily with a clear success check. Terra: traffic that fails Luna's success check; at half Sol's rates, test it there before you default to Sol. Sol: the default for everything else: chat products, code generation, drafting, agentic sessions. If you only pick one tier, pick Sol and push the easy traffic down to Luna. Astra: the requests where a wrong answer costs real money or engineering time and Sol has already failed. The expensive mistake is running Sol on work Luna handles: on our task profiles it costs about 20x Luna.
The trap in tier-splitting by hand
The honest catch: assigning traffic to tiers is a standing job, not a one-time decision. Failure rates move, prices change (Anthropic's Sonnet 5.5 now matches Sol's rates exactly), and every failed cheap run bills you twice. That per-request assignment problem is exactly what a blended model automates; ours publishes its benchmark scores so the claim is checkable. If you would rather keep the assignment manual, the cost calculator prices any split across these tiers and their Anthropic rivals.
The exact questions people search
What is the difference between GPT-6.1 Sol and GPT-6 Luna?
Price and how hard a problem each tier solves reliably. GPT-6.1 Sol is the production tier at $2 input / $10 output per million tokens. GPT-6.1 Terra is the mid tier at $1/$5, half Sol's rates. GPT-6 Luna is the volume tier at $0.10/$0.50, a twentieth of Sol's rates. GPT-6 Astra sits above all three at $10/$50 for the hardest work.
Is there still a mid tier between Sol and Luna?
Yes. GPT-6.1 Terra lists at $1 input / $5 output per million tokens, with cached input at $0.05: half Sol's rates and ten times Luna's. GPT-6.1 Sol at $2/$10 covers most production traffic, Luna takes the volume work, Terra takes what Luna misses, and Astra is the premium option above them.
Which is cheaper, GPT-6 Luna or Claude Haiku 4.5?
Luna, by a wide margin on list price: $0.10/$0.50 per million tokens against Haiku's $1/$5. On a short extraction task that is roughly $0.00015 versus $0.0015. Quality on your own traffic decides whether the saving holds.
Which is cheaper, GPT-6.1 Sol or Claude Sonnet 5.5?
Neither on list price: both cost $2 input / $10 output per million tokens, and both bill cache reads at $0.10. Token use and failure rate on your workload decide the real bill.
Compare any two models
VS
List rates and dated competitor measurements: prices and measured bills. Preliminary Pareto 26.10 benchmark costs per task from October 1, 2026 are on the model card. Verbosity: Edition 2.
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