OpenAI API Pricing (2026): GPT-6.1 Sol and Three App Budgets

OpenAI API pricing makes GPT-6.1 Terra the first model to evaluate for a small team's routine coding agent: $1 per million input tokens, $0.05 cached input and $5 output. Routing focused support and Batch summaries to GPT-6 Luna while trying Terra for coding brings the illustrative monthly base budget to $114.40, before cache-write uplifts. Keep GPT-6.1 Sol for complex coding and GPT-6 Astra for the hardest work when avoided rework justifies their higher bills.

Verified against OpenAI's API pricing page, detailed rate sheet and model documentation on October 27, 2026. Workload volumes remain explicit assumptions; the calculations use the current rates.

Since October 26, 2026, GPT-6.1 Terra has been available as gpt-6.1-terra. OpenAI says its Standard API prices are 50% below GPT-5.6 Terra and GPT-6.1 Sol, and it launched the same day for Plus, Pro, Enterprise and Edu users in ChatGPT Work and Codex. That changes the starting model to evaluate, not the need to check its work. Source: OpenAI's announcement.

OpenAI API is the usage-billed interface your application calls. Its bill depends on what goes into the model, what comes out, and which paid tools the application uses.

OpenAI API Pricing: Current Model Rates

GPT-6.1 Terra costs $1 input, $0.05 cached input and $5 output per million tokens. OpenAI positions it for visual reasoning, computer use and writing. Sol remains the complex-coding option, Luna the focused, high-volume option and Astra the choice for the most demanding work.

The following covers the models featured on OpenAI's business API pricing page, rather than its entire model catalog. Token rows are USD per 1M tokens. Time rows explicitly show minutes and seconds. The four flagship text rows use Standard processing at up to 272K input tokens per request; model documentation applies the long-context premium above that boundary. Cache-write rates are separate input categories, detailed below.

Source: OpenAI API pricing, verified October 27, 2026. “Not listed” means the source does not provide that rate; it does not mean a free output allowance. “Not split” means the displayed price is time-based rather than separated into token directions.

GPT-6 Sol is not listed in the featured business-page price rows. Its name is distinct from GPT-6.1 Sol, so this snapshot does not silently assign it the newer model's rates. Embedding rates and other models outside that featured set remain outside this price sheet.

Terra's model page lists a 1,050,000-token context window and 128,000 maximum output tokens. It accepts text and images and produces text; audio and video are not supported model inputs. Tool calling requires the Responses API. The maximum context is a capacity limit, not permission to price a million-token request at the short-context rate.

Which Model Should a Small Team Default To?

Start routine coding and computer-use features with a Terra evaluation; keep Sol for complex coding. The old blanket Sol recommendation no longer fits the price ladder. At the original coding volumes, Terra's base bill is $95 against Sol's $140. That $45 saving is useful only if the accepted work stays good enough.

Terra is a sensible candidate for a bounded code change, extracting information from a document, acting on an application screen or drafting text. Those patterns follow OpenAI's positioning, not an independent test. OpenAI reports 50.3% on Terminal-Bench 4.0 at maximum reasoning effort, against GPT-5.6 Terra's published 21.5%. These are vendor-reported results, and the same announcement says Sol and Astra remain better choices for the most complex coding tasks.

Keep Sol for complex, open-ended coding where a failed attempt creates expensive review and correction work. It costs $45 more than Terra in the coding example before cache-write uplifts. If Sol avoids more than that in rework, keep it. A passing benchmark score is not proof that Terra can replace your existing coding route.

Use Luna for a narrow job with a clear acceptance check. A support classifier that selects a known category or a summarizer whose output can be checked against its source is a better candidate than an open-ended coding task. Luna remains cheaper than Terra; a new model is no reason to move accepted focused work up the price ladder.

Keep Astra available for the most demanding reasoning and coding, especially when failures are expensive. Its coding base bill is $550, a $455 premium over Terra or $410 over Sol at identical billed usage. Pay that premium when your own completed-work results show enough avoided rework. A high price alone does not establish that it will.

For a team already using GPT-6 Sol, preserve its existing budget until you can compare billed usage and accepted results; the featured pricing page supplies no older-Sol migration saving. For GPT-5.6 Terra, OpenAI's API deprecations page lists no announced retirement as of October 27, 2026. Evaluate the upgrade on cost and results, without inventing a retirement deadline.

What Does One Million Tokens Cost?

There is no single price for one million OpenAI tokens. A token is a unit of material processed by the model. Input is the material sent in; output is the generated material billed back. Cached input is reused input that the API bills at the lower cached rate.

One million uncached input tokens plus one million output tokens costs $60 on Astra, $12 on Sol, $6 on Terra or $0.60 on Luna. That is two million billed tokens. One million total tokens split equally between uncached input and output costs $30, $6, $3 or $0.30 respectively.

To calculate a text-model bill, separate ordinary input, cache reads and cache writes:

Token cost = ordinary input / 1M × input rate + cached reads / 1M × read rate + 30-minute writes / 1M × 30-minute write rate + 12-hour writes / 1M × 12-hour write rate + output / 1M × output rate.

Ordinary input is total input minus cached reads minus cache writes. A write uses its own rate instead of the ordinary-input rate; adding both full charges double-counts those tokens. If writes have already been included at the ordinary rate in an estimate, add only the difference. Source: OpenAI prompt caching.

At Standard short-context rates, Terra writes cost $1.25 per million tokens for the default 30-minute lifetime or $2.50 for 12 hours. Sol's corresponding write rates are $2.50 and $5; Astra's are $12.50 and $25; Luna's are $0.125 and $0.25. These are minimum cache lifetimes, not guaranteed deletion deadlines, and the read rate is unchanged by the chosen lifetime. Source: detailed pricing.

On both Terra and Sol, cached input is 95% cheaper than ordinary input. But one million output tokens still costs as much as 100 million cached input tokens. A large cache saving does not justify unlimited generated material. Count billed output across the whole agent task, rather than budgeting only the final answer a user sees.

OpenAI API Pricing Calculator: Three Monthly Workloads

The three workloads have a $114.40 monthly base budget under the suggested routing, before cache-write uplifts. This is a planning example for a small app operator, not a measured production bill or a promise that the models produce equally good results.

Each individual request is assumed to stay at or below 272K input tokens. Cached volumes mean billed cache reads, and output includes all billed output across all calls. The stated input volumes include any billed search content. Tool activity is included where stated; subscription fees, hosting and other unspecified meters are outside these totals. The inputs are the current detailed OpenAI rates.

The original workloads specify fresh input and cache hits but no write counts. To keep the comparison like for like, the base totals below price all noncached input at the ordinary rate. They are not complete cache-inclusive bills. For each million of those tokens billed as writes instead, add 0.25 times the ordinary-input rate for 30-minute writes, or 1.5 times for 12-hour writes. The examples show the effect without guessing a cache-write volume for your app.

Support Bot: $13.90 Base on Luna, $47 on Terra

Assume 10,000 conversations per month. Across each conversation's calls, budget 1,000 fresh input tokens, 4,000 cached input tokens and 500 output tokens. Monthly totals are 10M fresh input, 40M cached input and 5M output. Assume another 1,000 web-search calls during the month.

On Luna, the tokens cost:

10 × $0.10 + 40 × $0.01 + 5 × $0.50 = $3.90.

The search calls add $10, bringing the base total to $13.90, or $1.39 per 1,000 conversations. With the same usage, Terra costs 10 × $1 + 40 × $0.05 + 5 × $5 = $37 in tokens plus $10 search, or $47, equivalent to $4.70 per 1,000 conversations. Sol costs $74 in tokens plus $10 search, or $84. Astra costs $390 in tokens plus $10 search, or $400.

Luna is the economical candidate if the bot handles a bounded support job and its answers pass your acceptance checks. This bill assumes the reusable material qualifies for cached billing. With prompt caching disabled, all 50M input tokens use the ordinary rate: Luna's token subtotal becomes $7.50 and its total becomes $17.50. Terra would cost $85 with the same no-cache input and output volumes. Separately, if all 10M noncached input tokens are billed as 30-minute writes, the cached-case base totals rise from $13.90 to $14.15 on Luna, or from $47 to $49.50 on Terra. Record both cache reads and writes before treating caching as a saving.

Coding Agent: $95 Base on Terra, $140 on Sol

Assume 1,000 coding tasks per month. Across all turns of each task, budget 15,000 fresh input tokens, 100,000 cached input tokens and 5,000 output tokens. The month therefore uses 15M fresh input, 100M cached input and 5M output. A task can contain multiple requests; these are task totals.

Also assume 2,000 web-search calls and 1,000 container sessions, each using 1 GB and the source's 20-minute session unit.

Terra's base token bill is:

15 × $1 + 100 × $0.05 + 5 × $5 = $45.

Search calls cost $20, and containers cost 1,000 × $0.03 = $30. The base total is $95 per month, or $0.095 per task. Search content is already included in the assumed input volumes; otherwise its tokens must be added.

At identical billed volumes, Sol costs 15 × $2 + 100 × $0.10 + 5 × $10 = $90 in tokens plus $50 in tools, totaling $140, or $0.14 per task. Astra costs $500 in tokens plus $50 in tools, totaling $550. Luna costs $5 in tokens plus $50 in tools, totaling $55.

If all 15M noncached tokens are billed as 30-minute cache writes, Terra's total becomes $98.75 and Sol's becomes $147.50. With 12-hour writes, substitute that higher write rate in the same formula. A cache hit has a low rate; creating and renewing the cache is not free.

The cheaper model does not remove the tool bill. Switching from Sol to Terra saves $45 in the base case, not half of the $140 app bill. Moving from Terra to Luna saves another $40, provided Luna completes acceptable work. Sol and Astra earn their respective $45 and $455 premiums over Terra when they avoid more than that in rework. That is the decision rule a token-only comparison cannot supply.

Batch Summarizer: $5.50 on Luna, $55 on Terra

Assume 20,000 documents per month, each with 4,000 uncached input tokens and 300 output tokens. That produces 80M input and 6M output tokens. Assume prompt caching is disabled for these one-off documents, so there are no cache reads, writes or tool charges. The summaries can be processed asynchronously over the Batch API's 24-hour window.

Luna's Standard token cost would be 80 × $0.10 + 6 × $0.50 = $11. Applying the source's 50% Batch discount gives $5.50 per month, or $0.275 per 1,000 summaries.

On Terra, Standard processing would cost 80 × $1 + 6 × $5 = $110; Batch or Flex halves the token rates, giving $55, or $2.75 per 1,000 summaries. The same Batch volumes cost $110 on Sol and $550 on Astra. Use the cheaper model when the summaries meet the required standard; move individual difficult documents to a stronger model when their correction cost warrants it. A customer waiting for an immediate reply is a different workload and should not be budgeted as asynchronous Batch work.

The Combined Monthly Budget

The suggested base route totals $13.90 Luna support + $95 Terra coding + $5.50 Luna Batch summaries = $114.40. The previous Sol-coding route was $159.40 at those same base assumptions, a $45 difference. If all noncached support and coding tokens are instead billed as 30-minute writes, the new route becomes $118.40.

Using Terra for all three has a $197 base cost: $47 support, $95 coding and $55 Batch summaries. Using Sol for all three costs $334; Astra costs $1,500; Luna costs $74.40, provided its work is acceptable. Each comparison excludes cache-write uplifts. These comparisons hold billed token and tool volumes constant; they do not assume the models take the same number of attempts in practice.

For an app operator, that distinction decides the bill. A model needing more turns can consume more input, output, search calls and sessions. Compare cost per accepted conversation, completed coding task or usable summary before applying the lowest rate to the entire product.

OpenAI Batch API Pricing and Data Residency

Terra's Batch and Flex rates are half Standard; Fast mode doubles Standard; regional processing adds 10% where available. The Terra model page also applies a long-context premium to the full request when input exceeds 272K tokens: double input and cache rates, and 1.5 times output. These prices are not limited to the tokens beyond the threshold.

The following Terra rates are USD per million tokens, before any regional premium. Paired cells show the two named meters in the stated order.

Source: OpenAI detailed pricing and Terra's model page; long-context mode rows are calculated from their stated multipliers. Cache-write lifetimes are minimum retention periods, not guaranteed expiry times.

Batch runs work asynchronously over 24 hours. It fits overnight document summaries, categorization and other jobs whose deadline permits that window. Flex offers the same token discount in exchange for slower responses and occasional resource unavailability. Fast is the paid speed option. Choose the service mode for the deadline, rather than applying Batch prices to an interactive feature. Source: processing options.

Regional processing multiplies applicable model-token rates by 1.10 where available. For Terra's $45 coding model subtotal, that produces $49.50, an extra $4.50, before cache-write adjustments. The same percentage applies to the applicable long-context or service-mode token rates; do not automatically apply it to the separate search-call or container bill. Regional availability remains a deployment constraint, not something a price multiplier guarantees.

Tools Can Set the Cost Floor

Count search calls and container sessions separately from model tokens. A token estimate can be correct while the monthly budget remains too low because a task invokes additional paid resources.

OpenAI Web Search API Pricing

Web search costs $10 per 1,000 calls, plus search content tokens billed at model rates in the detailed API rate sheet. That is $0.01 per call: 100 calls cost $1; 10,000 cost $100, before those tokens. The business pricing page still says search content is free; use the more specific API tool-pricing rules for the budget. The examples above include retrieved content within their stated input volumes, rather than assuming a free input allowance.

In the support example, 1,000 searches cost more than the entire Luna token subtotal. Make search frequency a deliberate product choice. A reply that genuinely needs current information can justify a search; a reply using an already supplied support policy should not automatically inherit a search budget.

Containers: The Session Is the Billing Unit

Containers, execution environments used alongside models, cost $0.03 for 1 GB or $1.92 for 64 GB, per 20-minute session per container. The pricing page dates that session billing to March 31, 2026, which has passed in this October snapshot. Its older “Now” wording is not a reason to assume one permanent fee per container. Source: OpenAI API pricing.

The coding example deliberately assumes 1,000 one-GB sessions. It does not claim that every coding task consumes exactly one session. Count your sessions as their own meter, especially when tasks use several containers or span more session units.

At the listed 64-GB rate, those 1,000 sessions would cost $1,920. Keeping the same Sol tokens and search calls would raise the coding base month from $140 to $2,030, before cache-write uplifts. Terra with those larger containers would cost $45 + $20 + $1,920 = $1,985 on the same base assumptions. The larger container's session fee is 64 times the smaller one's. The detailed rate sheet also lists 4 GB at $0.12 and 16 GB at $0.48 per 20-minute session. It says eligible sessions are billed by the minute with a 5-minute minimum; the examples here explicitly assume full 20-minute sessions. Source: detailed container pricing.

OpenAI Realtime API Pricing

GPT-Realtime-2.1 uses different prices for audio, text and image input. Audio tokens are a voice billing meter; they should not be treated as text tokens or converted to minutes with an unsupported rule.

One million uncached audio input tokens plus one million audio output tokens costs $32 + $64 = $96 on GPT-Realtime-2.1. The same token volumes cost $10 + $20 = $30 on GPT-Realtime-2.1 mini. Text and image inputs use their own rows in the table. Source: OpenAI API pricing.

For time-based work, GPT-Live-1 is the conversation model, GPT-Live-Transcribe handles live speech-to-text, GPT-Transcribe handles asynchronous transcription, and GPT-Realtime-Translate handles realtime translation. Using the displayed minute rates, 1,000 minutes costs $50, $17, $4.50 or $34 respectively. Those are different jobs, not interchangeable voice plans. These figures cover the listed time meter only; the detailed pricing page bills GPT-Live backend model and tool usage separately. The page gives no conversion that turns the Realtime audio-token example into an equivalent number of minutes.

OpenAI Image API Pricing

GPT-Image-2.5 Sunburst and GPT-Image-2.5 Flare have the same listed token rates. Both charge $8 for image input, $2 for cached image input and $30 for image output per million tokens; text prompts cost $5 input or $1.25 cached input. OpenAI positions Sunburst around editing precision and Flare around everyday generation speed. Source: OpenAI API pricing.

An assumed one million generated image tokens plus one million uncached text-prompt tokens costs $30 + $5 = $35 on either model. That does not mean one million images. The pricing page says images are converted to tokens but does not establish one fixed token count per generated image for this calculation.

Budget image work from its actual billed image and text meters. Avoid promising a fixed per-image charge from a per-token row, or selecting between these models on a price difference this page does not show.

Subscriptions, Free Access and Other Billing Questions

A ChatGPT subscription does not pay your application's API bill. OpenAI explicitly separates API billing from ChatGPT Plus, Business, Enterprise and Edu. Use the ChatGPT pricing guide for the subscription decision, and budget app usage separately.

OpenAI Codex API Pricing

Codex is OpenAI's coding product; the relevant distinction is how you pay for its use. When budgeting separately billed API activity, use the model, token and tool meters above. Product-plan allowances are a different purchase. The Codex pricing guide covers that subscription decision.

Buying a seat for a developer does not turn the support bot, automated coding workload or batch summarizer into prepaid app usage. Keep product subscription spending and the application's metered API spending as separate budget lines.

OpenAI API Pricing Free Tier

The retrieved pricing page lists no general free API token allowance. It explicitly says Playground usage, the browser interface for trying requests, is billed like regular API usage. Do not budget experimentation as free merely because it happens outside your app.

Someone using only a free ChatGPT experience may never need to buy API usage. Once your app makes paid API requests, that free-app choice is no basis for a free production budget.

This source does not state a universal API student discount, an API refund policy, credit expiry or an annual token-price commitment. Those omissions are not proof that no account-specific offer or separate policy exists. They mean this pricing snapshot cannot promise one. In particular, do not import a subscription's refund or annual-billing terms into an API budget.

Set Next Week's Budget From Completed Work

Evaluate Terra for routine work, retain Sol for complex coding, and measure the entire task. Your next budget should use observed billed usage rather than the number of words in the final reply.

1. 1

   Record a baseline

   For representative work, record ordinary input, cache reads, cache writes by lifetime, billed output, searches and container sessions across every turn. Keep the task's acceptance result alongside its cost.

2. 2

   Move bounded work where it fits

   Try Luna for focused tasks whose results can be checked. Put work that can wait into Batch. Retain the route only when the output meets its acceptance criteria.

3. 3

   Price the upgrade against rework

   For difficult tasks, compare Sol's or Astra's additional API cost with the value of corrections it avoids. Use the actual attempts and tool usage, not an assumption that every model consumes identical tokens.

OpenAI's pricing FAQ says monthly budget enforcement can be delayed and you remain responsible for overage. Treat the configured budget as a spending control with that stated limitation, and monitor actual usage. For project structure and recovery workflows, see the API budget controls guide.

Frequently Asked Questions

How much does OpenAI cost?

OpenAI API usage is metered by model, tokens and tools. For Standard requests up to 272K input tokens, Terra is $1 input, $0.05 cached input and $5 output per million tokens; Sol is $2, $0.10 and $10 respectively. Terra cache writes cost $1.25 per million tokens for 30 minutes or $2.50 for 12 hours, replacing the ordinary-input rate for those tokens. There is no single app-wide monthly price on this API price sheet.

Is ChatGPT API cheaper than ChatGPT Plus?

It depends on usage and what you need. An app's API bill can be small, but it buys metered application requests rather than the subscription product experience. OpenAI states that API usage is billed separately from ChatGPT subscriptions.

What are the pricing and cost comparisons for different LLM APIs?

Normalize input, cached input, output, tool use and successful completion before comparing providers. The like-for-like OpenAI coding base scenario here costs $55 on Luna, $95 on Terra, $140 on Sol and $550 on Astra, before cache-write uplifts and with quality held as an acceptance condition. This snapshot contains no verified prices for other providers.

Is it worth paying for OpenAI?

It is worth paying when accepted work saves more than API usage and resulting rework cost. Evaluate Terra for routine coding, retain Sol for complex coding, and escalate to Astra when avoided corrections justify its additional cost. Use Luna where its work passes the required checks.

Is it worth to pay $20 for ChatGPT?

Pay for a ChatGPT subscription when its features and the time it saves justify the fee. It does not purchase the app usage calculated here, so that API spending remains a separate decision.

Is OpenAI API free or paid?

The page lists paid model and tool usage and no general free API allowance. It also says Playground requests are billed like regular API requests. A free ChatGPT experience does not establish free API usage.

Is OpenAI API expensive?

The job and its tool activity decide. The hypothetical support base month costs $13.90 on Luna, while coding costs $95 on Terra or $140 on Sol, before cache-write uplifts. These figures depend on the stated billed volumes; a small token rate does not remove search or container charges.

What are the best free AI APIs?

No general free OpenAI API allowance is listed on this pricing page. Luna is a low-cost paid option for focused tasks whose outputs pass your checks. A provider's free API allowance needs its own current verification before it belongs in a production budget.

How much is 1 million tokens OpenAI?

At Standard short-context rates, one million ordinary input tokens costs $10 on Astra, $2 on Sol, $1 on Terra and $0.10 on Luna. One million output tokens costs $50, $10, $5 and $0.50 respectively. One million input plus one million output is two million billed tokens, totaling $60, $12, $6 or $0.60; cache writes use their separate input rates.

Does OpenAI offer an API student discount?

No universal API student discount is stated on the pricing page verified for this article. Do not count a student offer for another OpenAI product as API credit unless its own terms explicitly provide that benefit.

What is OpenAI's API refund policy?

The verified pricing page does not state an API refund policy. This article therefore does not promise refunds or apply ChatGPT subscription rules to API purchases.

Has OpenAI API pricing changed in 2026?

GPT-6.1 Terra launched on October 26, 2026 at $1 input, $0.05 cached input and $5 output per million tokens. OpenAI says its Standard API prices are 50% below GPT-5.6 Terra and GPT-6.1 Sol. This is a new model option, not a claim that Sol's own rates were cut. The pricing page also dates per-20-minute container-session billing to March 31, 2026.

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