Random Number Generator
Generate random numbers within specified range, supporting integers, decimals, and batch generation
Set parameters and click "Generate Random Numbers" to start
• Range Setting：Minimum value must be less than maximum value
• Generation Count：Supports 1-1000 random numbers
• Decimal Places：0 means integer, supports up to 10 decimal places
• Click Numbers：Click any generated number to copy to clipboard
• Quick Settings：Provides quick configuration for common scenarios
Your Privacy is Protected
All generation runs locally in your browser. We do not store or transmit your data.
What is a Random Number?
A random number is a value produced without a predictable pattern. There are two kinds. True random numbers come from physical processes — radioactive decay, thermal noise, atmospheric radio — and are fundamentally unpredictable. Pseudo-random numbers are generated by a mathematical formula and only appear random.
Almost every tool you use, including this generator, produces pseudo-random numbers. The formula starts from a seed (often the current time) and churns out a long sequence that passes statistical tests for randomness. For games, simulations, classroom activities, and casual draws, pseudo-randomness is more than good enough — and it has the advantage of being fast and repeatable when you want it to be.
The key limitation to remember: pseudo-random generators are not secure for cryptography. Predictable seeds mean predictable sequences, which an attacker could exploit.
How Random Numbers in a Range Are Generated
Most generators first produce a decimal between 0 (inclusive) and 1 (exclusive). Converting it into your desired range uses this formula:
Float in a range:
value = random() × (max − min) + min
Integer in a range:
value = floor(random() × (max − min + 1)) + min
Examples:
Dice (1–6): floor(0.547 × 6) + 1 = 3 + 1 = 4
Percentage (0–1, 2 decimals): 0.7183 → rounded to 0.72
Integer vs decimal: an integer result rounds to a whole number (useful for dice, draws, IDs). A decimal result keeps fractional detail (useful for percentages, coordinates, and scientific sampling).
Common Use Cases
Dice, cards, and raffles — Simulating a six-sided die, picking a winner from a list, or drawing a playing card all boil down to choosing a random integer in a fixed range.
Sampling and statistics — Researchers draw random samples from a population so every member has an equal chance of being selected, which is the basis of unbiased surveys and controlled experiments.
Simulations and modeling — Monte Carlo methods run millions of random trials to estimate everything from project risk to particle physics. Random inputs let a model explore a realistic range of outcomes.
Games and decisions — Enemy behavior, loot drops, board-game moves, and even “flip a coin to decide” all rely on randomness to keep outcomes fair and unpredictable.
Frequently Asked Questions
Is Math.random() truly random?
No. Math.random() and most random number generators in programming are pseudo-random — they use a deterministic formula and a seed value to produce a sequence that only looks random. Given the same seed, they produce the exact same sequence. For games, simulations, and most apps this is perfectly fine. True randomness requires a physical source such as radioactive decay or electronic noise.
How do I generate random numbers without repeats?
To draw unique numbers, create a list of all candidates (e.g., 1–50), shuffle it, and take the first N values. This is called sampling without replacement. Simply rejecting duplicates while generating works for small ranges, but becomes slow as the range fills up. Our tool does not deduplicate by default — if you need a lottery-style draw, generate within a range at least as large as the count you want.
Are these random numbers cryptographically secure?
No. Browser-based generators like Math.random() are not suitable for passwords, tokens, or security keys, because their output can be predicted if the internal state is known. For security purposes, use a cryptographically secure generator — in the browser that is window.crypto.getRandomValues(), and in Node.js it is the crypto module. Never use Math.random() for anything an attacker could exploit.
How do I simulate a die roll or coin flip?
For a six-sided die, generate a random integer from 1 to 6. For a coin, use 0 or 1 (or map them to heads/tails). The trick is converting a 0–1 decimal into a whole number in your range: multiply by the number of sides, take the floor, and add 1. Our quick settings include a preset for a 1–6 die, so you can roll instantly.
Why did the generator output the same number twice in a row?
This is normal and expected. In true randomness, repeats happen often — if you roll the same die twice, there is a 1 in 6 chance the second roll matches the first. A sequence that avoids repeats would actually be less random, not more. Over a large number of draws, each value appears roughly equally often, but in the short term streaks and duplicates are part of genuine randomness.