Base text-token estimate, not an invoice. Excludes reasoning beyond the word estimate, output overshoot, cache writes/storage, tools, regional surcharges and editing. Unsupported tiers use Standard and say so. Check the calculation assumptions and budget for human editing.
Prompts over 272K input tokens bill at 2x input / 1.5x output for the whole session.
One 1,500-word article costs $0.00080 on GPT-5 nano, OpenAI's cheapest tracked model, and $0.3627 on GPT-5.4 Pro, its most expensive. On GPT-5 nano, Batch costs $0.00040 at these assumptions.
Cheapest first. These are list rates applied to a token model — see
the methodology for exactly where that diverges from an invoice.
The 1,000w column is the per-1,000-words figure people quote: $0.00054 on GPT-5 nano at these settings.
How OpenAI prices
What is specific to this provider
Providers do not price the same way, and the differences change which model wins.
Rate structure
The shape of the lineup
OpenAI has by far the widest range of any provider we track — the most expensive
model costs hundreds of times the cheapest per article. Sol, Terra and Luna have
separate prices. Reasoning settings and generated token counts can still change a bill;
this word-based estimate does not add a separate reasoning allowance. The newest entry is
GPT-6 Astra, released 2026-09-03 and priced level
with Anthropic's top model rather than against GPT-5.5.
Processing tiers
What discounts exist
Fast pricing is model-specific (roughly 1.67×–2.5× the Standard
rate across the tracked catalog). Flex uses the half-price rate with slower
synchronous scheduling; Batch is asynchronous at 50% off. Availability is
model-specific, not a universal Pro-family rule: check the calculator and model documentation.
These estimates exclude regional pricing uplifts; Astra Fast is unavailable with EU data residency.
Context pricing
Where the rate changes
The 1,050K-context models carry a threshold most calculators miss: a prompt over
272K input tokens bills at 2× input and 1.5× output for the whole session,
not just the excess. Article workflows sit far below it, but a retrieval pipeline that
stuffs a research corpus into context can cross it without anyone noticing.
Watch out
What to check before you budget
Two things. Three Pro-tier models publish no cache-read rate at all, so prompt
caching cannot reduce their input cost — if a workflow depends on caching a large shared
system prompt, that rules them out regardless of quality. And GPT-5.6 Sol's current
$4 / $20 is promotional, published as available only at least through 21 November
2026 with no successor rate named, so an annual budget built on it is provisional.
What these rates buy
Read an unedited OpenAI draft before you budget
Every gallery below includes an unedited GPT-5 nano and GPT-5.5 draft, published
blind with a current-rate cost comparison. The model and the price stay hidden until you
reveal them, so this page can name who took part without spoiling which draft is which.
GPT-5.4
Prompts over 272K input tokens bill at 2x input / 1.5x output for the whole session.
$2.50
$0.250
$15.00
1,050K
GPT-5.6 Sol
Promotional rate, published as available at least through 2026-11-21; OpenAI has not announced the rate that follows it. Prompts over 272K input tokens bill at 2x input / 1.5x output for the whole session.
$4.00
$0.400
$20.00
1,050K
GPT-5.5
Prompts over 272K input tokens bill at 2x input / 1.5x output for the whole session.
$5.00
$0.500
$30.00
1,050K
GPT-6 Astra
Prompts over 272K input tokens bill at 2x input / 1.5x output for the whole session.
$10.00
$1.000
$50.00
1,050K
GPT-5.6 Cyber
Security-focused tier, gated behind the Daybreak program.
$12.50
$1.250
$75.00
1,050K
GPT-5.5 Cyber
Security-focused tier, gated behind the Daybreak program.
Answers specific to this provider's rate structure.
Which GPT model is cheapest for article writing?
GPT-5 nano is the cheapest tracked model from any provider for a full-length draft. It is priced for classification and extraction work rather than long-form prose, so treat its output as a first draft that needs real editing.
What is the difference between the Fast, Flex and Batch tiers?
They are service levels for the same model, but not every model supports every tier. OpenAI Fast rates vary by model in the tracked catalog; Flex and Batch are 50% off where listed. Batch is asynchronous with up to 24-hour turnaround, while Flex is synchronous with slower scheduling. The calculator exposes only the tiers published for the selected model.
Does reasoning effort change the price?
No. OpenAI replaced the effort dial with separate models: Sol, Terra and Luna are the effort tiers and each publishes its own rate. Changing an effort setting does not change per-token billing, though a model that emits more reasoning tokens will bill more output.
What is the 272K token threshold?
On the 1,050K-context models, a prompt over 272K input tokens bills at 2x input and 1.5x output for the entire session — not just for the tokens above the line. Article workflows sit far below it, but a retrieval pipeline that loads a large corpus can cross it unnoticed.
Why do some GPT models show no cached-input rate?
The Pro-tier models publish no cache-read rate, so prompt caching cannot reduce their input cost. We leave the column empty rather than assuming a percentage. If your workflow depends on caching a large shared prompt, those models are ruled out on structure regardless of quality.
The bottom line
OpenAI is one column in a five-column decision
Price your workflow here, then check it against the other providers before committing.
At article volumes the difference between two reasonable models is usually smaller than a
single hour of editing. When the work can run asynchronously, compare OpenAI's batch rate — not its standard rate — against DeepSeek, where no Batch tier is published. DeepSeek instead offers a separate off-peak discount.