What Is llm-prices.com (LLM Pricing Calculator)?

Updated

llm-prices.com is a free web-based calculator for estimating the cost of an LLM API call. You enter token counts and per-million-token prices, and it returns a total cost. It also includes a comparison table of model prices per million tokens. It is a third-party tool with source code on GitHub, not an official pricing page from any model provider — so treat its numbers as a starting estimate and confirm against the provider's own pricing before you commit to a budget.

How the calculator works

The tool is built around one simple cost model: tokens × price per million tokens. You provide three inputs and three matching prices.

Inputs (token counts):

  • Number of input tokens (also called prompt tokens)
  • Number of cached input tokens
  • Number of output tokens (also called completion tokens)

Prices (per million tokens, in dollars):

  • Cost per million input tokens
  • Cost per million cached input tokens
  • Cost per million output tokens

Output:

  • Total cost for the call, combining all three components

The formula the tool implies is:

total = (input_tokens        / 1,000,000) * input_price
      + (cached_input_tokens / 1,000,000) * cached_price
      + (output_tokens       / 1,000,000) * output_price

Cached input is billed separately because providers typically charge less for tokens that hit a prompt cache. If your workload doesn't use caching, set the cached token count to zero.

The model price table

Below the calculator, the page shows a Model prices (per million tokens) table with columns for:

  • Model
  • Input cost
  • Cached cost
  • Output cost
  • A Compare Prices action

You can filter the table with Show just selected or reset it with Clear selection, so you can line up only the models you actually care about. The table carries a "last updated" timestamp, which tells you how fresh the listed prices are.

When to use it

Use llm-prices.com when you want a quick, provider-agnostic estimate:

  • Sizing a feature before you build it. Plug in your expected prompt and completion lengths to see whether a task is cheap or expensive at scale.
  • Comparing two or three models. Select them in the table and compare input/output costs side by side.
  • Checking the effect of caching. Run the same token counts with and without cached input to see how much caching could save.

Skip it when you need a binding number. It is a calculator, not a quote.

Limitations to keep in mind

  • Tokenizer differences. The page itself notes that different models use different tokenizers, so direct token-based price comparisons may not be entirely accurate. The same text can produce different token counts across models.
  • Prices change. The table has a "last updated" timestamp; if it's stale, the per-million-token figures may no longer match what providers charge.
  • It's third-party. The source is on GitHub, and the page links to it. That's useful for verifying the math, but it also means the tool is maintained independently of any provider.
  • No account or billing features. It estimates cost; it doesn't connect to your API account or track real usage.

Practical workflow

  1. Estimate your token counts — from a tokenizer, your logs, or a rough words-to-tokens rule of thumb.
  2. Enter the three token counts and the three per-million prices for your target model.
  3. Read the total cost.
  4. Repeat with a second model's prices to compare.
  5. Confirm the final numbers against the provider's official pricing page before budgeting.