Big Number Calculator — Exact Arithmetic with Unlimited Digits (BigInt)
Free tool for exact arithmetic on huge integers with no rounding error. Powered by JavaScript BigInt, it correctly computes addition, subtraction, multiplication, integer division (quotient and remainder), and exponentiation even beyond 9,007,199,254,740,991 (2^53 − 1).
Why precision breaks down beyond 2^53
A regular calculator or JavaScript's Number type can no longer distinguish adjacent integers once you go past 2^53 (Number.MAX_SAFE_INTEGER). BigInt lets you compute exactly, even beyond that limit.
| Number.MAX_SAFE_INTEGER | 9,007,199,254,740,991(253 − 1) |
|---|---|
| 9007199254740992 + 1 | Number: 9007199254740992(誤り) / BigInt: 9007199254740993(正確) |
Tips
- Regular calculators and spreadsheets lose precision beyond 2^53 (about 9 quadrillion), but this tool uses BigInt to compute exactly with no digit limit.
- Integer division (÷) shows both the quotient and the remainder, which is handy for double-checking modular arithmetic used in cryptography and hashing.
- Exponents are capped at 1,000,000 for safety — an unbounded exponent could make the browser unresponsive.
- You can paste numbers with thousand-separator commas (e.g.
1,234,567) — they are stripped automatically before calculation. - Click "Insert sample" to auto-fill an example that exceeds 2^53, so you can immediately see the difference from an ordinary calculator.
FAQ
Side Note — Why Computers Struggle With Really Big Numbers
Computer number representation has long had a hard limit. The 64-bit floating-point type (double precision) used by default in most programming languages can only safely represent integers up to 2^53 − 1 (9,007,199,254,740,991), because its mantissa has just 53 bits. Beyond that, rounding errors creep in whenever such an integer is represented. Our own Calculator tool has this same precision limit.
Arbitrary-precision integers ("bignums") solve this problem. Around 2020, JavaScript added a new BigInt type to every major browser, allowing exact integer arithmetic with no digit limit other than available memory. Internally, a bignum is stored as an array of digit chunks, so computation time grows as the number of digits grows — there is a real trade-off between exactness and speed.
This technology is essential in cryptography. RSA keys, for instance, commonly use 2048-bit integers (over 600 decimal digits), and arbitrary-precision integer libraries are used worldwide to compute the multiplications and modular exponentiations such keys require.
Competitive programming frequently involves huge factorials (100! has 158 digits) or distant terms of the Fibonacci sequence. Ordinary numeric types accumulate error partway through such calculations, so fluency with bignums often separates a correct solution from an incorrect one.