AI Token Cost Calculator
Estimate your GPT, Claude, and Gemini API costs before you spend a single dollar — paste your prompt, pick a model, and see the real price.
$5/1M input tokens · $30/1M output tokens · Context: 1,048,576 tokens
Used to project your monthly cost (assumes 30 days).
Input Cost
$0.0050
Output Cost
$0.0150
Total Cost / Request
$0.0200
Projected Monthly Cost
Based on your requests/day input
$60.00
Compare All Models
Cost for the same 1,000 input / 500 output tokens, cheapest first.
| Model | Provider | Input Cost | Output Cost | Total Cost | Context Window |
|---|---|---|---|---|---|
| Gemini 2.5 Flash-Lite (legacy)Cheapest | $0.0001 | $0.0002 | $0.0003 | 1,000,000 | |
| GPT-4o mini | OpenAI | $0.0002 | $0.0003 | $0.0005 | 128,000 |
| GPT-5.6 Luna | OpenAI | $0.0002 | $0.0006 | $0.0008 | 1,048,576 |
| Gemini 3.5 Flash-Lite | $0.0003 | $0.0013 | $0.0016 | 1,048,576 | |
| Claude Haiku (legacy) | Anthropic | $0.0008 | $0.0020 | $0.0028 | 200,000 |
| Claude Haiku 4.5 | Anthropic | $0.0010 | $0.0025 | $0.0035 | 200,000 |
| GPT-5.2 | OpenAI | $0.0009 | $0.0035 | $0.0044 | 400,000 |
| Gemini 3.6 Flash | $0.0015 | $0.0038 | $0.0052 | 1,048,576 | |
| Claude Sonnet 5 | Anthropic | $0.0020 | $0.0050 | $0.0070 | 1,000,000 |
| GPT-4o | OpenAI | $0.0025 | $0.0050 | $0.0075 | 128,000 |
| GPT-5.6 Terra | OpenAI | $0.0020 | $0.0060 | $0.0080 | 1,048,576 |
| Gemini 3.1 Pro | $0.0020 | $0.0060 | $0.0080 | 1,048,576 | |
| Claude Sonnet (legacy 4.6) | Anthropic | $0.0030 | $0.0075 | $0.0105 | 200,000 |
| Claude Opus 5 | Anthropic | $0.0050 | $0.0125 | $0.0175 | 1,000,000 |
| GPT-5.6 Sol | OpenAI | $0.0050 | $0.0150 | $0.0200 | 1,048,576 |
| Claude Fable 5 | Anthropic | $0.0100 | $0.0250 | $0.0350 | 1,000,000 |
| Claude Opus (legacy) | Anthropic | $0.0150 | $0.0375 | $0.0525 | 200,000 |
AI APIs are billed by token, not by request or by word, which makes real costs easy to underestimate — especially once output length, system prompts, and daily request volume are factored in. This AI token cost calculator estimates what a given prompt will actually cost across the major providers, so you can compare GPT, Claude, and Gemini pricing side by side and catch an expensive model choice before it shows up on your bill.
How the estimate is calculated
We count tokens the way providers bill them
Your text is split using each model's own tokenizer, not a word-count guess. That's the same unit OpenAI, Anthropic, and Google use to generate your invoice, so the number you see here is the number that shows up on your bill.
Input and output are priced separately
Every major provider charges more for what the model generates than for what you send it — often 3 to 5 times more. We apply each model's current published input and output rate to your exact token counts, not a blended average.
You get a real monthly number
Add your expected requests per day and the calculator projects a monthly spend, so you can catch an expensive model choice before it's baked into your product — not after the first invoice.
What actually moves your AI API bill
The headline per-token rate is only half the story. These two factors explain most of the gap between what people expect to pay and what they actually get billed.
Output length is usually the bigger lever
A short prompt with a long, detailed response often costs more than a long prompt with a one-line answer. If your bill is higher than expected, check output length before you blame input size.
Cached and repeated context costs less
If your app resends the same system prompt or reference document on every call, prompt caching can cut that portion of the input cost by 80–90% on providers that support it. This calculator estimates standard rates; check your provider's caching pricing separately.
AI API pricing changes frequently as providers release new models and adjust rates. We update this page as new pricing is announced, but for production budgeting, always cross-check against the provider's official pricing page linked from the model selector above.
Frequently Asked Questions
How accurate is this AI token calculator?
Token counts come from each provider's own tokenizer logic, so they closely match what you'd see on your actual API bill. Pricing reflects each provider's publicly listed rates at the time of writing — always confirm against the provider's official pricing page before a large-scale deployment, since rates change and providers sometimes offer volume, cached-input, or batch discounts this calculator doesn't model.
Why do GPT, Claude, and Gemini charge different prices for input vs. output tokens?
Generating text costs more compute than reading it, so every major provider prices output tokens higher than input tokens — commonly 3 to 5 times more. A short prompt that triggers a long, detailed answer can end up costing more than the input token count alone would suggest.
What's a token, in plain terms?
A token is a chunk of text — often a word or part of a word — that a model processes as one billing unit. English text averages roughly 4 characters per token, but this varies by language and content type, which is why an exact tokenizer count is more reliable than a rough word-count estimate.
Which AI model is cheapest for high-volume use?
It depends on your workload, but as a rule of thumb: lighter, faster models built for high-volume tasks (classification, extraction, routing, simple chat) are priced far below flagship reasoning models. Route the bulk of your traffic to a cheaper model and reserve the expensive flagship for tasks that genuinely need it — this single change is usually the biggest lever on your bill.
Does this calculator send my text anywhere?
No. Tokenization and cost calculation run entirely in your browser — your text isn't uploaded, logged, or stored.
Why do costs here look different from what I'm seeing in my provider dashboard?
Differences usually come from cached-input pricing, batch API discounts, system prompts or tool-call overhead not included in your test input, or a rate change on the provider's end since this page was last updated. Use this calculator for quick estimates and planning, and your provider's billing dashboard for exact spend.
LLM Pricing Calculator
"LLM pricing" isn't one number — it's several different pricing models stacked on top of each other: pay-as-you-go API billing, flat consumer subscriptions, negotiated enterprise contracts, and the fixed-cost alternative of self-hosting an open model. Which one applies to you changes the entire calculation. Growfiy's calculator focuses on the API pricing model — the one that actually scales with your usage — and this page walks through where it fits against the alternatives.
Useful if you're trying to figure out whether you need a subscription, an API key, or an enterprise conversation in the first place.
The Four LLM Pricing Models
- Pay-as-you-go API: billed per token (input and output priced separately), scales directly with usage, no monthly cap — this is what Growfiy's calculator estimates.
- Flat consumer subscription: a fixed monthly fee (like ChatGPT Plus or Claude Pro) for using the provider's own chat interface, with soft usage limits rather than per-token billing.
- Enterprise / committed-use contracts: negotiated pricing based on guaranteed volume, often bundled with SLAs, dedicated support, or custom model access — not listed on public pricing pages.
- Self-hosted open-source models: no per-token fee at all — cost shifts to GPU/infrastructure and engineering time, which only becomes economical at high, steady usage volumes.
Which Pricing Model Fits You
- Individual user, occasional use: a flat subscription is usually simpler and cheaper than metering usage through the API.
- Building a product or feature: the API is your only option — subscriptions don't offer programmatic access.
- Growing startup with rising usage: start on API pricing, track your monthly spend, and reach out for enterprise terms once volume becomes significant.
- Very high, predictable volume: it's worth evaluating self-hosted open models against API costs, since fixed infrastructure can become cheaper at scale.
Frequently Asked Questions
What's the difference between API pricing and a subscription like ChatGPT Plus?
A consumer subscription (like ChatGPT Plus or Claude Pro) charges a flat monthly fee for usage inside that provider's own app, with soft usage limits. API pricing is pay-as-you-go per token, meant for building your own product on top of the model, with no bundled interface and costs that scale directly with usage.
When does it make sense to use the API instead of a subscription?
If you're building a product or automation that calls the model programmatically, you need the API — subscriptions don't offer this. If you're a single user just chatting with the model directly, a subscription is usually cheaper and simpler than metering your own usage through the API.
Do LLM providers offer volume discounts for high usage?
Larger providers often have enterprise or high-volume pricing tiers with negotiated rates, batch processing discounts, or committed-use pricing, but these are typically arranged directly with sales rather than published on the standard pricing page — worth inquiring about once your usage crosses a meaningful threshold.
Is self-hosting an open-source LLM cheaper than using a paid API?
It depends on your volume and scale. Self-hosting shifts cost from per-token API fees to fixed infrastructure (GPUs, hosting, maintenance, engineering time), which can be cheaper at very high, steady volume but often costs more than API pricing at low-to-moderate usage once you account for setup and operational overhead.
Why do enterprise LLM contracts not show public pricing?
Enterprise agreements are usually customized around committed usage volume, SLAs, support tiers, and sometimes model customization, so providers negotiate these case by case rather than publishing a fixed rate — this is standard practice across most B2B software with usage-based pricing.
How do I estimate my own cost if I'm not sure which pricing model fits?
Start with the pay-as-you-go API estimate using the calculator above, since it reflects true usage-based cost with no bundling. If your estimated monthly spend approaches or exceeds a subscription's flat fee for a single-user case, or crosses into high-volume territory, that's the signal to evaluate subscriptions or enterprise pricing instead.