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 common 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 way of the API, and customary short-context pricing per million tokens breaks down within the desk under.
| 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 quite 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 affords all three fashions to Plus and better plans. Customary ChatGPT conversations work otherwise: Terra and Luna should not selectable there, and eligible paid customers attain Sol by way of the Medium, Excessive, and Further Excessive reasoning choices, based mostly on their plan. OpenAI’s present Assist Heart lists Sol Professional, a higher-quality variant for the toughest duties, as obtainable 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 quite 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 charge 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 fees GPT-5.5 by no means billed. OpenAI studies increased scores and decrease output-token use on a number of coding and computer-use evaluations, though the comparability is dependent upon the benchmark, reasoning setting, and competing mannequin. An actual bill is dependent 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 crucial mannequin for enterprise consumers
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 value and with 16% fewer tokens. Deal with the determine as a customer-reported outcome from one firm’s workloads, not a common benchmark each staff will replicate. Terra is price a migration take a look at on present brokers earlier than Sol turns into the default assumption for brand 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 seemingly dwelling for Luna is high-volume, low-complexity work: buyer help triage, content material classification, extraction, and light-weight coding help, the place throughput and price per name matter greater than peak reasoning high quality.
Luna isn’t robotically low cost in follow. Output nonetheless prices six instances enter at customary charges, so a verbose Luna deployment can rack up spend sooner 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 must 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 charge, whereas a cache write prices 1.25 instances the uncached enter charge. Steady system prompts, device definitions, and reference materials turn out to be low cost to reuse after the primary write; prompts altering on each name could rack up write fees 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 fees twice the usual enter charge and 1.5 instances the usual output charge for the whole request, not solely the portion above the brink. Sol due to this fact 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 charge.
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 charge 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 resembling classification, extraction, and enrichment tolerant of slower or asynchronous execution.
Precedence processing doubles the usual short-context charge: 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 consumers mustn’t assume the identical multiplier extends past 272,000 enter tokens till OpenAI paperwork a long-context Precedence tier. Precedence could justify its price in latency-sensitive, customer-facing purposes, however a staff budgeting round customary pricing and deploying Precedence by default can shortly double its model-token spend.
Regional processing introduces one other price layer. OpenAI fees a ten% uplift for eligible data-residency fashions launched on or after March 5, 2026, although regional storage availability doesn’t robotically imply mannequin inference occurs inside the chosen area.
Mannequin tier is just one routing resolution. Sol additionally affords max, which spends extra compute on deeper reasoning than its excessive setting, and extremely, which coordinates 4 brokers by default. Extremely can end tough work sooner, however parallel execution can elevate combination token use. Sol’s reasoning mode features as one other FinOps management, not a easy high quality change.
Programmatic Software 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 way of the mannequin. In tool-heavy workflows, OpenAI studies fewer tokens and fewer mannequin spherical journeys in consequence. Price management now occurs at a number of layers, not one.
Efficiency per greenback wants workload testing
Vendor benchmarks describe circumstances OpenAI controls, not a purchaser’s precise site visitors. OpenAI’s comparability desk studies 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 extensive 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 beneath totally different settings, a reminder: reasoning configuration modifications the rating as a lot because the mannequin does. OpenAI generated the figures by way of its analysis harness, and so they deserve attribution as such quite than remedy as impartial proof.
A procurement resolution wants a corporation’s inner eval set: activity success charge, human correction time, whole tokens consumed, latency, retry charge, and price per accomplished activity quite 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 sooner can nonetheless burn extra tokens in combination. Impartial, cross-enterprise proof for uniform price financial savings, latency good points, 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 funds planning. Procurement coverage now must specify which mannequin handles which information class, which reasoning stage will get authorised by default, when Precedence processing is allowed, and what occurs when a smaller mannequin’s confidence drops. Organizations benchmarking full workflows towards inner duties, quite 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.
