Random Number Generator

Yes — by default this tool uses window.crypto.getRandomValues(), which is cryptographically secure (CSPRNG). It is suitable for generating passwords, tokens, and security-sensitive values. The seeded mode uses the Mulberry32 PRNG which is not cryptographically secure but is deterministic and high-quality for simulations.

Uniform: every value in [min, max] is equally likely — standard dice rolls, sampling. Normal (Gaussian): values cluster around a mean with standard deviation controlling the spread — models heights, test scores, measurement errors. Exponential: values cluster near the minimum with an exponential drop-off — models inter-arrival times, component lifetimes.

In unique mode, the same number will not appear twice in a single generation. This is equivalent to sampling without replacement — useful for lottery-style picks, random permutations, or selecting items from a list. Note: you cannot generate more unique integers than there are integers in the range.

A seeded PRNG produces the same sequence every time for the same seed value. This makes results reproducible — useful for scientific simulations, A/B testing, and debugging. Enter any text or number as the seed. The same seed always yields the same output.

Up to 10,000 numbers per generation. For large batches, the tool shows a frequency distribution histogram and summary statistics (min, max, mean, median, standard deviation) instead of listing every number.

Yes — use the Copy button to copy all numbers to the clipboard as comma-separated values, or export as CSV (with index column) or JSON (includes generation parameters).