Budget before launch
Estimate support chatbot, RAG, coding agent, summarization, and classification costs before you commit to a provider or model tier.
AI Tools · API budget planning
LLM API Cost Calculator
Estimate the cost of GPT, Claude, Gemini, Grok, DeepSeek, Llama, and Mistral API workloads. Compare input, output, cached prompt, batch, monthly, yearly, and blended token costs in one place.
Pricing disclaimer: Prices are local planning data last reviewed April 27, 2026. Provider pricing changes often, so verify official pages before production budgeting.
Workload inputs
Use-case presets
Choose models to compare
Cost comparison
| Model | Input | Output | Request | Day | Month | Year | Blended / 1M | Cache saved | Context used |
|---|
Why this calculator is useful
Compare the real workload mix
Input and output tokens often have different prices. Blended cost shows the effective price for your actual ratio, not a generic model headline price.
Model caching savings
Repeated system prompts, policies, examples, and reference material can qualify for cached input rates on some providers. Use the cache slider to test the savings.
Catch context risks
The table flags how much of each model's context window your request uses, so you can avoid oversized prompts or choose a larger-context model.
How to use this calculator
- Estimate tokens per request. Use the token counter for exact text, or start from a preset if you only need a quick budget.
- Enter traffic volume. Requests per day and billing days determine the monthly and yearly projection.
- Adjust cache and batch settings. Use cached input when repeated prompt material is likely. Use batch pricing for offline jobs where latency is not important.
- Select realistic models. Compare up to six models you can use in your app, then sort visually by monthly spend.
- Export or share. Copy the share URL for teammates or download a CSV for a spreadsheet budget.
Pricing sources
These calculations use local pricing metadata so the page works offline. Always verify the exact model, region, caching rules, batch discounts, and long-context thresholds on official provider pages before relying on estimates.
Frequently asked questions
What is a token?
A token is the billing unit most LLM APIs use. It can be a word, word fragment, punctuation mark, or code symbol.
Why are output tokens more expensive?
Output tokens require the provider to run the model while generating each response. That serving cost is often higher than reading input.
What is cached input pricing?
Cached input pricing is a lower rate for repeated prompt content that the provider can reuse. It is useful for long system prompts, examples, policy text, and repeated reference material.
What is blended cost per 1M tokens?
Blended cost combines input, cached input, and output token prices into one effective price for your entered workload.
How accurate are these numbers?
The formulas are exact for the local prices, but provider pricing changes. Treat results as planning estimates and verify official pricing before production decisions.
Related AI Tools
LLM API Cost Calculator practical guide
LLM cost is estimated from input tokens, output tokens, request volume, and the selected model price. This section gives visitors enough context to understand the calculation, choose the right inputs, and decide whether the result is suitable for a rough estimate, a worksheet answer, or a planning discussion.
How to use this AI tool
- Start with the value you know best and confirm the unit shown beside the input field.
- Fill only the fields requested by the tool. If a field is optional, use it when it changes the real-world result, such as time, rate, power factor, credits, or serving count.
- Press calculate, then read the main result together with any secondary values, conversions, warnings, or examples on the page.
- Run one simple test case before using the result in a report. A quick mental check catches unit mistakes and misplaced decimals.
Formula or method used
Choose the model, enter average input and output tokens, add requests per day or month, then compare the projected total with a cheaper or smaller-context alternative. The important habit is to keep every input on the same basis before comparing results. For example, do not mix hours with minutes, grams with kilograms, square feet with square meters, or apparent power with real power unless the calculator explicitly converts those units.
Worked example
If a workflow sends 2,000 input tokens and receives 500 output tokens per request, multiply both values by request count and apply the model's input and output token rates separately. This kind of small example is useful because it makes the direction of the calculation clear. After the result looks sensible, replace the sample numbers with your real project, class, recipe, prompt, or equipment data.
When this page is useful
Use LLM API Cost Calculator for API budgeting, SaaS feature planning, chatbot estimates, batch summarization costs, and model switching decisions. It is also helpful when you need a fast second opinion before copying numbers into a spreadsheet, invoice, lab note, design brief, homework solution, or project estimate.
Accuracy tips
- Prefer measured values over rounded or advertised values whenever accuracy matters.
- Write down the unit beside each number so the same calculation can be checked later.
- Round final answers to a sensible number of digits; too many decimals can look more accurate than the inputs really are.
- Use professional guidance for legal, tax, medical, electrical installation, or safety-critical decisions.
Common mistakes to avoid
The most common errors are entering the right number in the wrong unit, forgetting a multiplier such as 1,000, using a default rate that does not match your location, or treating an estimate as a certified result. If the answer seems surprisingly high or low, halve or double one input and see whether the output changes in the expected direction. That simple sensitivity check helps visitors trust the tool and understand the relationship between inputs and results.
Mini FAQ
Can I use this result directly?
For learning, planning, and quick comparisons, yes. For compliance, contracts, tax filing, health decisions, or electrical work, treat the result as a starting point and verify it against official guidance or a qualified professional.
Why do two calculators sometimes give slightly different answers?
Differences usually come from rounding, default assumptions, unit conversions, or whether the tool includes optional factors. Check the formula, input units, and rounding method before deciding which result is more appropriate.