Numbers too big for an ordinary calculator, computed exactly.

Why ordinary calculators go fuzzy

Most calculators store numbers as 64-bit floating point, which holds about 15–17 significant digits exactly. Beyond that, digits are silently discarded.

Ask a normal calculator for 2²⁰⁰ and you get 1.606938e+60 — correct to seven digits and wrong about the other fifty-four. The exact answer is 1606938044258990275541962092341162602522202993782792835301376, and this tool gives all of it.

It is not a rounding preference. The information is genuinely gone: the format has nowhere to keep it.

Where the difference matters

• Cryptography. RSA keys are 2048-bit numbers — over 600 digits. Approximation is useless; a key that is nearly right is simply wrong.
• Combinatorics. Factorials explode. 20! is 2,432,902,008,176,640,000, already at the edge of exact float range. 21! is past it.
• Money at scale. This is why financial systems store amounts as integer cents rather than decimals — integers stay exact where fractions drift.
• Checksums and IDs. A credit card check digit or an ISBN depends on every digit. One silently dropped and the validation fails.

Whole numbers only

This uses BigInt, which is exact but integer-only. Division returns the whole-number quotient with the remainder available separately — 7 ÷ 2 gives 3 remainder 1, not 3.5. That is a deliberate trade: exactness at any size, in exchange for no fractions.

For decimals, ordinary floating point is fine — the Basic Calculator or Scientific Calculator will serve you better.

Why does a normal calculator lose digits on large numbers?

Because it stores values as 64-bit floating point, which holds roughly 15 to 17 significant digits. Anything beyond that cannot be represented, so it is dropped. The result is displayed in exponential form, correct at the front and wrong behind it.

Can this handle decimals?

No. It uses BigInt, which is exact but works only on whole numbers. Division gives the integer quotient, with the remainder available as a separate operation. For decimal arithmetic use the Basic or Scientific Calculator.

How large a number can it handle?

Far larger than anything you are likely to need — the limit is memory rather than a fixed digit count. Factorial is capped at 10,000 and exponents at 100,000 here purely to keep the page responsive.

Why do financial systems store money as integers?

To avoid exactly this loss of precision. Storing £10.99 as 1099 pence keeps every value exact, whereas decimal floating point cannot represent many everyday amounts precisely and the error accumulates across transactions.