diff --git a/benches/benches/distr.rs b/benches/benches/distr.rs
index 63d6a1034ee..ec43e7e61cc 100644
--- a/benches/benches/distr.rs
+++ b/benches/benches/distr.rs
@@ -159,7 +159,7 @@ fn bench(c: &mut Criterion<CyclesPerByte>) {
     g.finish();
 
     let mut g = c.benchmark_group("zipf");
-    distr_float!(g, "zipf", f64, Zipf::new(10, 1.5).unwrap());
+    distr_float!(g, "zipf", f64, Zipf::new(10.0, 1.5).unwrap());
     distr_float!(g, "zeta", f64, Zeta::new(1.5).unwrap());
     g.finish();
 
diff --git a/rand_distr/CHANGELOG.md b/rand_distr/CHANGELOG.md
index 8e6cfff686b..fc597d47763 100644
--- a/rand_distr/CHANGELOG.md
+++ b/rand_distr/CHANGELOG.md
@@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Mark `WeightError`, `PoissonError`, `BinomialError` as `#[non_exhaustive]` (#1480).
 - Remove support for generating `isize` and `usize` values with `Standard`, `Uniform` and `Fill` and usage as a `WeightedAliasIndex` weight (#1487)
 - Limit the maximal acceptable lambda for `Poisson` to solve (#1312) (#1498)
+- Change parameter type of `Zipf::new`: `n` is now floating-point (#1518)
 
 ### Added
 - Add plots for `rand_distr` distributions to documentation (#1434)
diff --git a/rand_distr/src/zipf.rs b/rand_distr/src/zipf.rs
index 9d98458db08..45a8bf2b5cb 100644
--- a/rand_distr/src/zipf.rs
+++ b/rand_distr/src/zipf.rs
@@ -35,7 +35,7 @@ use rand::Rng;
 /// use rand::prelude::*;
 /// use rand_distr::Zipf;
 ///
-/// let val: f64 = rand::rng().sample(Zipf::new(10, 1.5).unwrap());
+/// let val: f64 = rand::rng().sample(Zipf::new(10.0, 1.5).unwrap());
 /// println!("{}", val);
 /// ```
 ///
@@ -92,16 +92,17 @@ where
     /// Construct a new `Zipf` distribution for a set with `n` elements and a
     /// frequency rank exponent `s`.
     ///
-    /// For large `n`, rounding may occur to fit the number into the float type.
+    /// The parameter `n` is typically integral, however we use type
+    /// <pre><code>F: [Float]</code></pre> in order to permit very large values
+    /// and since our implementation requires a floating-point type.
     #[inline]
-    pub fn new(n: u64, s: F) -> Result<Zipf<F>, Error> {
+    pub fn new(n: F, s: F) -> Result<Zipf<F>, Error> {
         if !(s >= F::zero()) {
             return Err(Error::STooSmall);
         }
-        if n < 1 {
+        if n < F::one() {
             return Err(Error::NTooSmall);
         }
-        let n = F::from(n).unwrap(); // This does not fail.
         let q = if s != F::one() {
             // Make sure to calculate the division only once.
             F::one() / (F::one() - s)
@@ -173,24 +174,24 @@ mod tests {
     #[test]
     #[should_panic]
     fn zipf_s_too_small() {
-        Zipf::new(10, -1.).unwrap();
+        Zipf::new(10., -1.).unwrap();
     }
 
     #[test]
     #[should_panic]
     fn zipf_n_too_small() {
-        Zipf::new(0, 1.).unwrap();
+        Zipf::new(0., 1.).unwrap();
     }
 
     #[test]
     #[should_panic]
     fn zipf_nan() {
-        Zipf::new(10, f64::NAN).unwrap();
+        Zipf::new(10., f64::NAN).unwrap();
     }
 
     #[test]
     fn zipf_sample() {
-        let d = Zipf::new(10, 0.5).unwrap();
+        let d = Zipf::new(10., 0.5).unwrap();
         let mut rng = crate::test::rng(2);
         for _ in 0..1000 {
             let r = d.sample(&mut rng);
@@ -200,7 +201,7 @@ mod tests {
 
     #[test]
     fn zipf_sample_s_1() {
-        let d = Zipf::new(10, 1.).unwrap();
+        let d = Zipf::new(10., 1.).unwrap();
         let mut rng = crate::test::rng(2);
         for _ in 0..1000 {
             let r = d.sample(&mut rng);
@@ -210,7 +211,7 @@ mod tests {
 
     #[test]
     fn zipf_sample_s_0() {
-        let d = Zipf::new(10, 0.).unwrap();
+        let d = Zipf::new(10., 0.).unwrap();
         let mut rng = crate::test::rng(2);
         for _ in 0..1000 {
             let r = d.sample(&mut rng);
@@ -221,7 +222,7 @@ mod tests {
 
     #[test]
     fn zipf_sample_large_n() {
-        let d = Zipf::new(u64::MAX, 1.5).unwrap();
+        let d = Zipf::new(f64::MAX, 1.5).unwrap();
         let mut rng = crate::test::rng(2);
         for _ in 0..1000 {
             let r = d.sample(&mut rng);
@@ -232,12 +233,12 @@ mod tests {
 
     #[test]
     fn zipf_value_stability() {
-        test_samples(Zipf::new(10, 0.5).unwrap(), 0f32, &[10.0, 2.0, 6.0, 7.0]);
-        test_samples(Zipf::new(10, 2.0).unwrap(), 0f64, &[1.0, 2.0, 3.0, 2.0]);
+        test_samples(Zipf::new(10., 0.5).unwrap(), 0f32, &[10.0, 2.0, 6.0, 7.0]);
+        test_samples(Zipf::new(10., 2.0).unwrap(), 0f64, &[1.0, 2.0, 3.0, 2.0]);
     }
 
     #[test]
     fn zipf_distributions_can_be_compared() {
-        assert_eq!(Zipf::new(1, 2.0), Zipf::new(1, 2.0));
+        assert_eq!(Zipf::new(1.0, 2.0), Zipf::new(1.0, 2.0));
     }
 }
diff --git a/rand_distr/tests/cdf.rs b/rand_distr/tests/cdf.rs
index 8eb22740e2b..86e926af00e 100644
--- a/rand_distr/tests/cdf.rs
+++ b/rand_distr/tests/cdf.rs
@@ -385,7 +385,7 @@ fn zipf() {
     let parameters = [(1000, 1.0), (500, 2.0), (1000, 0.5)];
 
     for (seed, (n, x)) in parameters.into_iter().enumerate() {
-        let dist = rand_distr::Zipf::new(n, x).unwrap();
+        let dist = rand_distr::Zipf::new(n as f64, x).unwrap();
         test_discrete(seed as u64, dist, |k| cdf(k, n, x));
     }
 }