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.
GPT vs Claude vs Gemini Cost Calculator
Choosing between OpenAI's GPT, Anthropic's Claude, and Google's Gemini usually comes down to two questions: which one handles your task well, and which one costs less for your volume of requests. Growfiy's calculator lets you enter the same prompt once and see the estimated cost across all three, side by side, so the decision is based on real numbers instead of general reputation.
Built for developers picking a default model for a new project, founders comparing vendor costs before committing to one API, and teams deciding whether to route different tasks to different providers.
How to Decide Between Them
Sticker price alone rarely tells the full story. A fair comparison weighs cost against what each model actually costs you to accomplish a task — including how verbose its typical responses are, since output tokens are usually priced higher than input tokens.
- For high-volume, simple tasks (classification, short summarization, basic Q&A) — the cheapest tier from any provider is usually sufficient; compare their lightweight models against each other rather than their flagships.
- For complex reasoning or long-context tasks — flagship models justify their premium more often here; compare cost per successful outcome, not just cost per token.
- For latency-sensitive applications — smaller, cheaper models typically respond faster, which can matter as much as raw cost for real-time features.
- For mixed workloads — routing tasks to different models by complexity often beats picking one provider for everything.
What Changes If You Switch Providers Later
Moving between GPT, Claude, and Gemini at the API level is generally straightforward, since all three follow a similar request/response pattern. What usually needs rework is prompt tuning — instructions that produce reliable output on one model may need adjustment on another — along with any provider-specific features like function/tool-calling schemas or structured output formats. Planning for this upfront makes it easier to switch later if pricing or performance shifts.
Frequently Asked Questions
Which is cheaper — GPT, Claude, or Gemini?
It depends on the specific model tier within each family rather than the provider as a whole. Each provider offers a range from a low-cost, lightweight model to a premium flagship model, so the fair comparison is tier-to-tier — a budget Gemini model against a budget GPT model, for example — not flagship-to-flagship pricing alone.
Does a higher price always mean better output quality?
Not necessarily for every task. Flagship models tend to handle complex reasoning, long context, and nuanced instructions better, but for straightforward tasks like classification, extraction, or short-form summarization, a cheaper mid-tier model from any of the three providers often performs close enough to justify the lower cost.
How do I compare costs fairly across GPT, Claude, and Gemini?
Compare using the same prompt and expected output length across each model's calculator estimate, since input and output tokens are priced separately and at different rates on every platform. A model that looks cheaper per token can end up costing more if it tends to generate longer responses.
Is it hard to switch between GPT, Claude, and Gemini later?
Switching providers is usually manageable at the API level since most use a similar request/response structure, but prompts tuned for one model's behavior may need re-testing on another, and any provider-specific features (like function calling formats) will need adjustment during migration.
Should I use one model for everything or mix providers?
Many teams route by task — a cheaper model for high-volume, low-stakes requests (like tagging or summarizing) and a premium model for tasks that need stronger reasoning or accuracy — which often lowers total cost without sacrificing quality where it matters most.
Do GPT, Claude, and Gemini offer free usage tiers?
Each provider has offered free or trial credits for new API accounts at various points, but the amount and terms change frequently, so it's worth checking each provider's current pricing page directly rather than relying on older information.