โper call
โper 1k calls
โcheapest tier
GPT-5 tiers โ same workload
Identical tokens and call volume, priced on each GPT-5 tier. Cheapest for this workload is highlighted.
| Tier | Input $/1M | Output $/1M | Cost / month |
|---|
โ ๏ธ GPT-5 reference pricing (2026): GPT-5.5 $5.00/$30.00, GPT-5 $1.25/$10.00, GPT-5 mini $0.40/$1.60, GPT-5 nano $0.10/$0.40 per 1M input/output tokens. Prices change and vary by tier, region, batch and cached input โ confirm on OpenAI's pricing page. Want every model side by side? Use the
full LLM price comparison or the
token cost calculator. ยท
Report outdated price โโ Last verified: 2026-07-24ยท Source: official provider pricing pageยท Auto-monitored โ report change โ
How GPT-5 API pricing works
GPT-5 is billed per token, split into input (your prompt plus any context you send) and output (everything the model writes back). On each tier, output costs several times more than input โ GPT-5 is $1.25 / 1M input and $10.00 / 1M output, an 8ร gap โ so the length of the answer is the single biggest lever on your bill. Capping max_tokens, asking for concise responses, and trimming system prompts all cut cost directly. Because GPT-5 is a reasoning model, the hidden reasoning tokens it generates before the final answer are billed as output too, so heavy step-by-step reasoning shows up on the bill even when the visible answer is short.
The second lever is tier choice. The family spans a wide price range: flagship GPT-5.5 at $5.00 / $30.00 for the hardest reasoning and long-form work, GPT-5 as the balanced default, GPT-5 mini at roughly a third of GPT-5's price for everyday tasks, and GPT-5 nano at $0.10 / $0.40 for classification, extraction and high-volume short replies. A common pattern is to run a cheaper tier by default and reserve GPT-5 or GPT-5.5 only for the requests that genuinely need frontier quality โ the table above shows exactly what each tier costs at your volume. To see GPT-5 against Claude, Gemini and the rest, use the LLM price comparison; for a from-scratch breakdown of how per-token billing adds up, read how LLM API pricing works or browse the Learn hub.
How this calculator works
The GPT-5 API Cost Calculator estimates what you will pay to run a workload through OpenAI's GPT-5 family. You enter the input tokens per call, output tokens per call, and calls per month, then pick a model tier. It multiplies your input and output token counts by that tier's separate per-token rates, adds them into a per-call cost, and scales that across your monthly call volume to project the total bill. Because it prices the same workload across GPT-5.5, GPT-5, GPT-5 mini, and GPT-5 nano side by side, you can see exactly how much each tier would cost before committing.
The key trade-off to watch is that output tokens usually cost several times more than input tokens, so a chatty, long-response workload can cost far more than the input size suggests. Try trimming your output token estimate and testing a smaller tier: mini or nano often handle simpler tasks at a fraction of the price, while the largest tier is worth reserving for calls that genuinely need it. Because costs scale linearly with volume, a small per-call saving compounds sharply once you reach high monthly call counts.
Frequently asked questions
How much does the GPT-5 API cost?
Reference pricing (2026) is GPT-5 at $1.25 per million input tokens and $10.00 per million output tokens. The flagship GPT-5.5 is $5.00 input / $30.00 output, while GPT-5 mini is $0.40 / $1.60 and GPT-5 nano is $0.10 / $0.40. Your bill is input tokens times the input price plus output tokens times the output price, multiplied by how many calls you make.
What is the difference between GPT-5, GPT-5 mini and GPT-5 nano?
They are the same family at different capability and price points. GPT-5 and GPT-5.5 are the frontier tiers for hard reasoning and long-form work; GPT-5 mini is roughly 3x cheaper than GPT-5 for everyday tasks; GPT-5 nano is the cheapest, aimed at classification, extraction and high-volume short replies. Match the tier to the task rather than defaulting to the top model.
Why is GPT-5 output more expensive than input?
On every GPT-5 tier the output (per-million) price is several times the input price. Reasoning tokens the model generates before its final answer are billed as output too, so verbose answers and heavy reasoning drive the bill. Capping max_tokens and asking for concise answers cuts cost directly.