Enter a minimum and maximum value, choose how many numbers you need, and this Random Number Generator produces a set of random integers instantly. Control whether duplicates are allowed and how results are sorted — low to high, high to low, or unsorted. Perfect for lotteries, games, classroom draws, or any situation where unbiased randomness matters.
Generated Numbers
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Count
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Smallest in Set
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Largest in Set
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Sum
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Average
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A random number generator (RNG) is a tool that produces numbers selected from a defined range with no predictable pattern. Computer-based RNGs are typically pseudo-random, meaning they use a mathematical algorithm to simulate randomness. For most everyday purposes — games, raffles, classroom activities — pseudo-random results are perfectly adequate.
Pseudo-random numbers are generated by a deterministic algorithm and are statistically random but technically reproducible. True random numbers are derived from unpredictable physical phenomena, such as atmospheric noise. For most applications like picking lottery numbers or playing games, pseudo-random numbers are completely sufficient.
Set the <strong>Allow Duplicates</strong> option to 'No — unique numbers only'. The generator will ensure every number in your result set appears only once. Note that if you request more unique numbers than exist within your min–max range, the count will be capped at the total available values.
This tool supports generating up to 100 random numbers per request. Simply enter the desired count in the 'How Many Numbers' field and click Generate.
Yes. The minimum and maximum fields accept negative values. For example, set Min to -100 and Max to 100 to generate numbers across that entire range including negatives and zero.
You can choose to display results unsorted (in the order they were generated), sorted from low to high, or sorted from high to low using the Sort Results dropdown. The underlying random selection is unaffected by the sort choice.
Common uses include running prize draws, lotteries, and sweepstakes; selecting random participants from a group; generating numbers for games, puzzles, or educational activities; statistical sampling; and creating random data for testing software or simulations.
Because each number is picked independently and randomly, the average of any small sample will vary from the theoretical midpoint. As you generate more numbers, the sample average will tend to converge toward the true midpoint of the range — this is known as the law of large numbers.