diff --git a/examples/cluster/plot_cluster_comparison.py b/examples/cluster/plot_cluster_comparison.py
index 802f3996bbe7e..8b52759c79018 100644
--- a/examples/cluster/plot_cluster_comparison.py
+++ b/examples/cluster/plot_cluster_comparison.py
@@ -41,7 +41,7 @@
 # Generate datasets. We choose the size big enough to see the scalability
 # of the algorithms, but not too big to avoid too long running times
 # ============
-n_samples = 1500
+n_samples = 500
 noisy_circles = datasets.make_circles(n_samples=n_samples, factor=0.5, noise=0.05)
 noisy_moons = datasets.make_moons(n_samples=n_samples, noise=0.05)
 blobs = datasets.make_blobs(n_samples=n_samples, random_state=8)
@@ -74,9 +74,9 @@
     "eps": 0.3,
     "damping": 0.9,
     "preference": -200,
-    "n_neighbors": 10,
+    "n_neighbors": 3,
     "n_clusters": 3,
-    "min_samples": 20,
+    "min_samples": 7,
     "xi": 0.05,
     "min_cluster_size": 0.1,
 }
@@ -89,18 +89,27 @@
             "preference": -240,
             "quantile": 0.2,
             "n_clusters": 2,
-            "min_samples": 20,
-            "xi": 0.25,
+            "min_samples": 7,
+            "xi": 0.08,
+        },
+    ),
+    (
+        noisy_moons,
+        {
+            "damping": 0.75,
+            "preference": -220,
+            "n_clusters": 2,
+            "min_samples": 7,
+            "xi": 0.1,
         },
     ),
-    (noisy_moons, {"damping": 0.75, "preference": -220, "n_clusters": 2}),
     (
         varied,
         {
             "eps": 0.18,
             "n_neighbors": 2,
-            "min_samples": 5,
-            "xi": 0.035,
+            "min_samples": 7,
+            "xi": 0.01,
             "min_cluster_size": 0.2,
         },
     ),
@@ -109,12 +118,12 @@
         {
             "eps": 0.15,
             "n_neighbors": 2,
-            "min_samples": 20,
+            "min_samples": 7,
             "xi": 0.1,
             "min_cluster_size": 0.2,
         },
     ),
-    (blobs, {}),
+    (blobs, {"min_samples": 7, "xi": 0.1, "min_cluster_size": 0.2}),
     (no_structure, {}),
 ]