Generate random numbers between any range instantly. Dice roller, coin flip, and lucky lottery picker included — all free, no ads.
A random number generator (RNG) is a tool that produces numbers without any predictable pattern. Whether you need a single number for a quick decision, a batch of numbers for a raffle, or dice rolls for a board game, an RNG does the job instantly — no paper, no dice, no spinning a wheel.
Our free online random number generator lets you set any minimum and maximum value, choose how many numbers to generate, and optionally ensure there are no duplicates. It also includes a dice roller, coin flip, and lucky lottery picker — everything you need in one place.
There are two fundamentally different types of random numbers: true random and pseudorandom.
True randomness comes from unpredictable physical processes. Examples include atmospheric noise (used by random.org), thermal noise in electronic circuits, radioactive decay, and photon arrival times in quantum optics. Because these processes are governed by chaotic or quantum-mechanical physics, the output is fundamentally unpredictable — not just difficult to predict, but impossible in principle.
True hardware random number generators (HRNGs) are used in cryptography, secure key generation, and high-stakes simulations where absolute unpredictability matters. They are typically hardware devices or specialized system calls (like /dev/random on Linux).
Pseudorandom number generators (PRNGs) use a deterministic algorithm starting from a seed value. Given the same seed, the same sequence is always produced. JavaScript's Math.random() — which powers this tool — is a PRNG. Modern browsers use algorithms like xorshift128+ which produce sequences that pass all standard statistical randomness tests.
For everyday uses — games, decisions, statistics class, giveaways, sampling — pseudorandom numbers are completely adequate. The sequences are so long and the distribution so uniform that they are indistinguishable from true randomness in practice.
The only scenarios where true randomness is essential are cryptographic key generation and situations where an adversary might try to predict outputs knowing your seed. For everything else, Math.random() is the right tool.
Math.random() returns a floating-point number between 0 (inclusive) and 1 (exclusive). To get an integer in the range [min, max], the standard formula is:
Math.floor(Math.random() * (max - min + 1)) + min
The +1 ensures the max value is included in the possible outputs (since Math.random() never returns exactly 1). The Math.floor() rounds down to the nearest integer, giving a uniform distribution over all integers from min to max inclusive.
V8 (Chrome/Node), SpiderMonkey (Firefox), and JavaScriptCore (Safari) all use variants of the xorshift128+ algorithm, which has a period of 2128 − 1 — meaning the sequence won't repeat for an astronomically long time.
Random numbers are the backbone of games. Dice rolls, card shuffles, random enemy spawns, loot drops, procedurally generated maps — all rely on RNGs. Digital dice rollers let you play tabletop RPGs, board games, or card games without physical components. Our dice roller shows realistic dot faces so you can use it at the table.
Can't decide between two options? Flip a coin. Choosing between multiple options? Generate a random number between 1 and N. Many people find that flipping a coin reveals their true preference: the moment the coin lands, they feel either relieved or disappointed — and that reaction tells them what they actually wanted. An RNG can serve the same purpose.
Running a raffle, picking a contest winner, or assigning prizes? Generate unique random numbers for each ticket or entrant. Our multi-number generator with no-duplicates mode is ideal — enter the number of participants as your max, set count to however many prizes you have, and generate.
Random sampling is fundamental to statistics. When you can't survey an entire population, you draw a random sample. Random assignment of subjects to experimental and control groups eliminates selection bias. Simulations like Monte Carlo methods use millions of random numbers to estimate probabilities of complex events.
Teachers use random number generators to call on students fairly, randomly assign group members, pick question numbers from a test bank, or create varied problem sets. Students use them for study randomization — e.g., shuffling flashcard order randomly.
While cryptographic applications need stronger randomness than Math.random() provides, generating random PIN codes, temporary passwords, or one-time tokens for non-critical applications is perfectly fine with a well-seeded PRNG. For true cryptographic use, prefer window.crypto.getRandomValues().
Generative art, procedural music, random story prompt generators, random color pickers — creative tools often rely on randomness to produce unexpected and interesting results. Randomness breaks predictable patterns and introduces novelty.
Physical dice are among the oldest random number generators in existence. Archaeological evidence of dice has been found in sites dating back over 5,000 years in Mesopotamia, ancient Egypt, and the Indus Valley. The six-sided cube die (d6) became standard because it offers equal probability for each face when balanced correctly.
Tabletop RPGs expanded the vocabulary of dice to include d4, d8, d10, d12, and d20 — each serving different probability distributions. Our online dice roller simulates standard d6 dice with accurate dot-face rendering, but you can use the main number generator for any polyhedral die by setting max to 4, 8, 10, 12, or 20.
A fair coin has two outcomes with equal 50% probability — the simplest possible random event. Coin flips have settled disputes, decided sporting events, and resolved deadlocks for centuries. Our animated coin flip simulates a real toss, flipping before landing on Heads or Tails. The result counter tracks your history of flips so you can see the distribution over many trials.
Interestingly, physical coin flips are not perfectly 50/50 — research by Diaconis, Holmes, and Montgomery showed that a coin is more likely to land the same face up as it started (about 51% of the time) due to the physics of the toss. Our digital version is perfectly fair.
The lucky lottery picker generates a set of unique numbers drawn from a pool — just like a real lottery draw. The default settings (pick 6 from 1–49) match the format of many common lotteries worldwide. You can customize both the pool size and the number of picks to match your specific lottery format.
Each number is shown as a colored ball for easy reading, and all numbers are guaranteed to be unique (no duplicates). While no random number picker gives you better odds than any other selection method — each combination has exactly the same probability — it does save you the trouble of picking numbers yourself and avoids unconscious biases toward "lucky" numbers.
Use Brite to track habits, set daily goals, and make better decisions — all organized in one beautiful app.
Download Brite FreeMath.random() function, which produces pseudorandom numbers. For most everyday uses — games, decisions, statistics, raffles — pseudorandom numbers are indistinguishable from true randomness. True hardware-based randomness requires specialized equipment that captures physical phenomena like radioactive decay or thermal noise. For cryptographic needs, use window.crypto.getRandomValues() instead.