There is no universal price for one AI token. For API use, the rate depends on the provider, model, and billing category—and your request’s total also depends on how many input and output tokens it uses, whether input is cached, and whether tools or other services incur separate charges. Most published text rates are quoted per million tokens, so the practical question is what your completed task costs, not the price of an isolated token.
How to calculate the cost of one API request
Use the rate card for the exact model and service mode you selected. Multiply each usage category by its matching rate, divide by one million when rates are quoted per million tokens, then add any separately billed services.
estimated request cost = (input tokens × input rate + cached input tokens × cached input rate + output tokens × output rate) ÷ 1,000,000 + separately billed tool or service charges
Use only categories that apply to that model. A provider may distinguish cache reads from cache writes, for example, and a tool or modality may have its own fee. Do not assume all prompt tokens are cached or that every provider counts text, images, audio, and other inputs identically. [OpenAI API pricing; Gemini API pricing; Anthropic API pricing]
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Published API rates show why a token has no fixed price
These USD list-price examples are snapshots from provider pricing pages, not a market average or a guarantee of your bill. Confirm the current model row, context, mode, and effective date before budgeting. Contract terms, endpoint, tier, discounts, and geography may affect the charge.
| Provider and model | Input per million tokens | Cached input per million tokens | Output per million tokens | Scope |
|---|---|---|---|---|
| OpenAI GPT-6 Sol | $2.00 | $0.20 | $10.00 | Short context, standard rates shown on the pricing page; check the selected service-mode row. [Source] |
| OpenAI GPT-6 Astra | $10.00 | $1.00 | $50.00 | Short context, flagship-table rates; check the current context and service-mode row. [Source] |
| Anthropic Claude Opus 4.5 API Standard Global | $5.00 | Cache hits and writes are listed separately | $25.00 | Anthropic list-price document dated May 27, 2026. Its Batch row lists $2.50 input and $12.50 output per million tokens. [Source] |
| Google Gemini 3.7 Flash paid Standard | $0.75 through Dec. 31, 2026; $1.50 from Jan. 1, 2027 | Separate context-caching and storage charges are listed | $3.75 through Dec. 31, 2026; $7.50 from Jan. 1, 2027 | Scheduled paid Standard rates on the Gemini API pricing page; verify the effective date and model. [Source] |
These rows are not a like-for-like comparison of model quality or workload cost. For instance, if a request uses 10,000 input tokens and 2,000 output tokens at the listed GPT-6 Sol short-context rates, with no cached input or extra charges, the estimate is ($2.00 × 10,000 + $10.00 × 2,000) ÷ 1,000,000 = $0.04. Actual usage and applicable rate-card rules determine the bill.
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What changes the amount you pay
Input and output mix
Input and output can have different rates, and output is substantially more expensive than input in the examples above. Estimate both separately rather than applying the input rate to every token in a conversation. [OpenAI; Google; Anthropic]
Prompt caching
Reused prompt prefixes may qualify for a lower cached-input rate, but eligibility is not the same as caching every input token. Cache writes or storage may also be billed. OpenAI describes automatic prompt caching for supported models when prompts exceed 1,024 tokens; that threshold does not guarantee that every token in every request is cached. [OpenAI pricing; OpenAI prompt caching]
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Processing mode
Batch or lower-priority processing can be discounted for some models, while faster or priority modes may cost more. Eligibility and rates vary by model, so use the rate row for the mode actually selected. [OpenAI; Google; Anthropic]
Long context and processing region
Some rate cards apply different prices once an input crosses a context threshold or when a regional endpoint is used. OpenAI says GPT-6 Astra requests over 272K input tokens are charged at 2× the input and cache rates and 1.5× the output rate for the full request. Its pricing documentation also lists a 10% uplift for eligible regional-processing and FedRAMP endpoints. Check the applicable endpoint and model rules before estimating a large request. [OpenAI API pricing; OpenAI pricing documentation]
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Tools and non-text inputs
Images, audio, video, search grounding, and other tools may be billed under separate rules or fees. For example, Google lists separate grounding and tool charges. Check whether the chosen tool’s fee is additional to token billing and how its inputs are counted. [Gemini API pricing]
Tokenization and reasoning
The same prompt can produce different token counts on different models. Models may also generate different output or reasoning quantities for the same task. A lower per-token rate therefore does not necessarily mean a lower bill for a completed task. OpenAI recommends testing representative tasks and comparing total tokens and cost. [OpenAI cost optimization guidance]
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Estimate your cost before relying on a budget
- Select the exact model, endpoint, and service mode. Make sure the rate card matches your intended configuration.
- Record usage by billing category. Capture input, output, cached input, and any other categories reported by the model response or rate card.
- Apply the matching rates. Multiply each category’s token count by its rate. If the rate is per million, divide the result by 1,000,000.
- Add other charges. Include separately billed tools, cache storage, or modality fees that apply.
- Check the conditions. Verify context thresholds, region, mode eligibility, account terms, and rate effective dates.
- Test a representative task. Compare the full cost to complete the same task, not just the input rate or visible answer length.
- Reconcile the estimate with usage. Compare it with the actual request usage and provider dashboard. OpenAI documents both account-level dashboard review and request-level usage inspection. [OpenAI usage tiers and usage; OpenAI request usage]
How to compare token prices fairly
Compare options using the same representative workload and include the factors that change its bill:
- Model capability for the task, alongside input and output rates.
- Cache read, cache write, and storage treatment.
- Context-length thresholds and their pricing effects.
- Batch, flex, priority, or fast-mode eligibility and cost.
- Region, endpoint, and contract terms.
- Separate tool and modality charges.
- Total cost to complete the task, using measured token usage.
A single input-rate column cannot establish which model is cheapest overall. [OpenAI cost optimization guidance; OpenAI API pricing; Gemini API pricing; Anthropic API pricing]
This pricing discussion concerns developer API usage. Consumer chat subscriptions may be billed differently and should not be inferred from API token rates.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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