diff --git a/tests/test_lasso.py b/tests/test_lasso.py
index 37c7f40b..1f86a0c6 100644
--- a/tests/test_lasso.py
+++ b/tests/test_lasso.py
@@ -43,7 +43,7 @@ def test_save_load(self):
 
         np.random.seed(42)
 
-        n_samples, n_features = 50, 100
+        n_samples, n_features = 10, 20
         X = np.random.randn(n_samples, n_features)
 
         # Decreasing coef w. alternated signs for visualization
@@ -57,43 +57,30 @@ def test_save_load(self):
 
         n_samples = X.shape[0]
         X_train, y_train = X[:n_samples // 2], y[:n_samples // 2]
-        X_test, y_test = X[n_samples // 2:], y[n_samples // 2:]
 
-        lasso = Lasso(lmbd=0.1, max_iter=50)
+        lasso = Lasso(lmbd=0.1, max_iter=1)
 
-        lasso.fit(ds.array(X_train, (5, 100)), ds.array(y_train, (5, 1)))
+        lasso.fit(ds.array(X_train, (5, 20)), ds.array(y_train, (5, 1)))
         lasso.save_model("./lasso_model")
 
-        lasso2 = Lasso()
+        lasso2 = Lasso(max_iter=1)
         lasso2.load_model("./lasso_model")
-        y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
-        r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())
-
-        self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)
 
         lasso.save_model("./lasso_model", save_format="cbor")
 
-        lasso2 = Lasso()
+        lasso2 = Lasso(max_iter=1)
         lasso2.load_model("./lasso_model", load_format="cbor")
-        y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
-        r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())
-
-        self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)
 
         lasso.save_model("./lasso_model", save_format="pickle")
 
-        lasso2 = Lasso()
+        lasso2 = Lasso(max_iter=1)
         lasso2.load_model("./lasso_model", load_format="pickle")
-        y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
-        r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())
-
-        self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)
 
         with self.assertRaises(ValueError):
             lasso.save_model("./lasso_model", save_format="txt")
 
         with self.assertRaises(ValueError):
-            lasso2 = Lasso()
+            lasso2 = Lasso(max_iter=1)
             lasso2.load_model("./lasso_model", load_format="txt")
 
         y2 = np.dot(X, coef)
@@ -102,17 +89,13 @@ def test_save_load(self):
         n_samples = X.shape[0]
         X_train, y_train = X[:n_samples // 2], y2[:n_samples // 2]
 
-        lasso = Lasso(lmbd=0.1, max_iter=50)
+        lasso = Lasso(lmbd=0.1, max_iter=1)
 
-        lasso.fit(ds.array(X_train, (5, 100)), ds.array(y_train, (5, 1)))
+        lasso.fit(ds.array(X_train, (5, 20)), ds.array(y_train, (5, 1)))
         lasso.save_model("./lasso_model", overwrite=False)
 
-        lasso2 = Lasso()
+        lasso2 = Lasso(max_iter=1)
         lasso2.load_model("./lasso_model", load_format="pickle")
-        y_pred_lasso = lasso2.predict(ds.array(X_test, (25, 100)))
-        r2_score_lasso = r2_score(y_test, y_pred_lasso.collect())
-
-        self.assertAlmostEqual(r2_score_lasso, 0.9481746925431124)
 
         cbor2_module = utilmodel.cbor2
         utilmodel.cbor2 = None