OpenAI didn’t launch one mannequin on July 9, 2026. It launched a three-tier worth menu, and the menu issues greater than any single benchmark rating within the launch notes. Sol, Terra, and Luna now let a purchaser route every activity to a mannequin priced for the job as a substitute of defaulting each request to the flagship.
Three fashions divide the workload
GPT-5.6 reached basic availability on July 9, 2026, following a restricted preview introduced in late June. The household splits into Sol, the flagship; Terra, a balanced on a regular basis possibility; and Luna, the quickest and least expensive of the three. Builders can attain all three by means of the API, and customary short-context pricing per million tokens breaks down within the desk beneath.
| Mannequin | Enter | Cached enter | Cache write | Output |
| Sol | $5.00 | $0.50 | $6.25 | $30.00 |
| Terra | $2.50 | $0.25 | $3.125 | $15.00 |
| Luna | $1.00 | $0.10 | $1.25 | $6.00 |
Entry varies by product and plan relatively than following one easy rule. In Codex, Free and Go customers can attain Terra, whereas Plus, Professional, Enterprise, and Enterprise customers can select amongst Sol, Terra, and Luna. ChatGPT Work gives all three fashions to Plus and better plans. Normal ChatGPT conversations work in another way: Terra and Luna should not selectable there, and eligible paid customers attain Sol by means of the Medium, Excessive, and Additional Excessive reasoning choices, primarily based on their plan. OpenAI’s present Assist Middle lists Sol Professional, a higher-quality variant for the toughest duties, as accessible to Professional, Enterprise, and Enterprise plans, although the unique launch announcement named solely Professional and Enterprise. OpenAI folded GPT-5.6 into eligible present ChatGPT plans relatively than introducing a brand new subscription tier, and customary ChatGPT subscription costs didn’t rise alongside the mannequin launch.
Sol retains GPT-5.5’s base worth
The usual short-context price for Sol, $5 enter and $30 output per million tokens, matches GPT-5.5’s headline pricing precisely. OpenAI is positioning Sol as a functionality and effectivity acquire with out elevating the sticker worth of its high mannequin.
The comparability stops on the sticker, although. GPT-5.6 provides cache-write costs GPT-5.5 by no means billed. OpenAI experiences greater scores and decrease output-token use on a number of coding and computer-use evaluations, though the comparability depends upon the benchmark, reasoning setting, and competing mannequin. An actual bill depends upon reasoning effort, device calls, context size, and the way a lot of a immediate will get cached, not on the 2 headline numbers alone.
Terra could also be an important mannequin for enterprise patrons
Terra prices half of Sol and lands on the precise customary pricing GPT-5.4 carried at launch: $2.50 enter, $15 output. For a big share of enterprise workloads, the positioning issues greater than Sol’s frontier scores, as a result of most manufacturing site visitors doesn’t want frontier reasoning.
Notion, quoted in OpenAI’s launch supplies, mentioned many brokers constructed on GPT-5.5 carry out simply as properly on Terra at half the worth and with 16% fewer tokens. Deal with the determine as a customer-reported outcome from one firm’s workloads, not a common benchmark each crew will replicate. Terra is value a migration take a look at on present brokers earlier than Sol turns into the default assumption for brand spanking new ones.
Luna creates a low-cost routing tier
Luna runs at one-fifth of Sol’s enter worth and one-fifth of its output worth: $1 and $6 per million tokens. The probably residence for Luna is high-volume, low-complexity work: buyer help triage, content material classification, extraction, and light-weight coding help, the place throughput and value per name matter greater than peak reasoning high quality.
Luna isn’t routinely low cost in observe. Output nonetheless prices six occasions enter at customary charges, so a verbose Luna deployment can rack up spend quicker than a concise Sol deployment dealing with fewer, shorter exchanges. OpenAI’s scores additionally present actual gaps between Luna and Sol on tougher evaluations, so routing selections have to weigh activity problem alongside quantity.
Caching and lengthy context reshape the invoice
GPT-5.6 introduces specific cache breakpoints and a 30-minute minimal cache life. Cached enter reads earn a 90% low cost off the uncached enter price, whereas a cache write prices 1.25 occasions the uncached enter price. Secure system prompts, device definitions, and reference materials grow to be low cost to reuse after the primary write; prompts altering on each name might rack up write costs with out sufficient reuse to offset them.
Lengthy-context requests set off a better pricing tier as soon as a immediate exceeds 272,000 enter tokens. OpenAI costs twice the usual enter price and 1.5 occasions the usual output price for your complete request, not solely the portion above the brink. Sol subsequently rises to $10 per million enter tokens and $45 per million output tokens, Terra rises to $5 and $22.50, and Luna rises to $2 and $9. Cache-write costs double together with the enter price.
A simplified instance illustrates the unfold. For a million uncached enter tokens and 250,000 output tokens at short-context customary charges, Sol prices roughly $12.50, Terra roughly $6.25, and Luna roughly $2.50. Actual payments will differ as soon as instruments, caching, reasoning effort, and regional processing enter the calculation.
Batch, Flex, and Precedence create one other pricing layer
Processing class multiplies the pricing grid once more. Batch and Flex processing cost half the usual short-context price throughout the GPT-5.6 household: Sol falls to $2.50 per million enter tokens and $15 per million output tokens, Terra to $1.25 and $7.50, and Luna to $0.50 and $3. Batch and Flex go well with workloads similar to classification, extraction, and enrichment tolerant of slower or asynchronous execution.
Precedence processing doubles the usual short-context price: Sol rises to $10 per million enter tokens and $60 per million output tokens, Terra to $5 and $30, and Luna to $2 and $12. OpenAI’s pricing web page reveals solely short-context Precedence charges, so patrons mustn’t assume the identical multiplier extends past 272,000 enter tokens till OpenAI paperwork a long-context Precedence tier. Precedence might justify its price in latency-sensitive, customer-facing functions, however a crew budgeting round customary pricing and deploying Precedence by default can shortly double its model-token spend.
Regional processing introduces one other price layer. OpenAI costs a ten% uplift for eligible data-residency fashions launched on or after March 5, 2026, although regional storage availability doesn’t routinely imply mannequin inference occurs inside the chosen area.
Mannequin tier is just one routing resolution. Sol additionally gives max, which spends extra compute on deeper reasoning than its excessive setting, and extremely, which coordinates 4 brokers by default. Extremely can end troublesome work quicker, however parallel execution can increase mixture token use. Sol’s reasoning mode features as one other FinOps management, not a easy high quality swap.
Programmatic Instrument Calling provides a second lever. OpenAI says GPT-5.6 can write and run light-weight packages coordinating instruments and filtering intermediate outcomes, as a substitute of routing each device response again by means of the mannequin. In tool-heavy workflows, OpenAI experiences fewer tokens and fewer mannequin spherical journeys consequently. Price management now occurs at a number of layers, not one.
Efficiency per greenback wants workload testing
Vendor benchmarks describe situations OpenAI controls, not a purchaser’s precise site visitors. OpenAI’s comparability desk experiences 52.7% for Sol on Brokers’ Final Examination and an index rating of 80 on the Synthetic Evaluation Coding Agent Index, with Terra and Luna trailing by broad margins on tougher duties and narrower margins on simpler ones. A separate part of OpenAI’s launch web page cites 53.6 for Sol on the identical examination underneath totally different settings, a reminder: reasoning configuration modifications the rating as a lot because the mannequin does. OpenAI generated the figures by means of its analysis harness, they usually deserve attribution as such relatively than therapy as impartial proof.
A procurement resolution wants a company’s inner eval set: activity success price, human correction time, complete tokens consumed, latency, retry price, and value per accomplished activity relatively than price per token. A mannequin costing extra per token can nonetheless price much less per accomplished job if it wants fewer retries, and a multi-agent or Extremely configuration ending quicker can nonetheless burn extra tokens in mixture. Unbiased, cross-enterprise proof for uniform price financial savings, latency beneficial properties, or production-performance enhancements doesn’t but exist outdoors OpenAI’s benchmark tables and the named buyer quotes cited right here.
The routing resolution is now a FinOps resolution
GPT-5.6’s three-tier construction pushes mannequin choice out of engineering-only territory and into finances planning. Procurement coverage now must specify which mannequin handles which information class, which reasoning degree will get permitted by default, when Precedence processing is allowed, and what occurs when a smaller mannequin’s confidence drops. Organizations benchmarking full workflows towards inner duties, relatively than a single leaderboard rating, will make the higher name on the place Sol earns its worth and the place Terra or Luna already do the job.