diff --git a/mlos_core/mlos_core/tests/spaces/adapters/llamatune_test.py b/mlos_core/mlos_core/tests/spaces/adapters/llamatune_test.py
index 9d73b6ba8c..e63ac7f28c 100644
--- a/mlos_core/mlos_core/tests/spaces/adapters/llamatune_test.py
+++ b/mlos_core/mlos_core/tests/spaces/adapters/llamatune_test.py
@@ -15,9 +15,16 @@
 from mlos_core.spaces.adapters import LlamaTuneAdapter
 
 
-def construct_parameter_space(
+# Explicitly test quantized values with llamatune space adapter.
+# TODO: Add log scale sampling tests as well.
+
+
+def construct_parameter_space(  # pylint: disable=too-many-arguments
+    *,
     n_continuous_params: int = 0,
+    n_quantized_continuous_params: int = 0,
     n_integer_params: int = 0,
+    n_quantized_integer_params: int = 0,
     n_categorical_params: int = 0,
     seed: int = 1234,
 ) -> CS.ConfigurationSpace:
@@ -28,10 +35,18 @@ def construct_parameter_space(
         input_space.add_hyperparameter(
             CS.UniformFloatHyperparameter(name=f"cont_{idx}", lower=0, upper=64)
         )
+    for idx in range(n_quantized_continuous_params):
+        input_space.add_hyperparameter(
+            CS.UniformFloatHyperparameter(name=f"cont_{idx}", lower=0, upper=64, q=12.8)
+        )
     for idx in range(n_integer_params):
         input_space.add_hyperparameter(
             CS.UniformIntegerHyperparameter(name=f"int_{idx}", lower=-1, upper=256)
         )
+    for idx in range(n_quantized_integer_params):
+        input_space.add_hyperparameter(
+            CS.UniformIntegerHyperparameter(name=f"int_{idx}", lower=0, upper=256, q=16)
+        )
     for idx in range(n_categorical_params):
         input_space.add_hyperparameter(
             CS.CategoricalHyperparameter(
@@ -53,6 +68,13 @@ def construct_parameter_space(
                 {"n_continuous_params": int(num_target_space_dims * num_orig_space_factor)},
                 {"n_integer_params": int(num_target_space_dims * num_orig_space_factor)},
                 {"n_categorical_params": int(num_target_space_dims * num_orig_space_factor)},
+                {"n_categorical_params": int(num_target_space_dims * num_orig_space_factor)},
+                {"n_quantized_integer_params": int(num_target_space_dims * num_orig_space_factor)},
+                {
+                    "n_quantized_continuous_params": int(
+                        num_target_space_dims * num_orig_space_factor
+                    )
+                },
                 # Mix of all three types
                 {
                     "n_continuous_params": int(num_target_space_dims * num_orig_space_factor / 3),
@@ -374,6 +396,12 @@ def test_max_unique_values_per_param() -> None:
                 {"n_continuous_params": int(num_target_space_dims * num_orig_space_factor)},
                 {"n_integer_params": int(num_target_space_dims * num_orig_space_factor)},
                 {"n_categorical_params": int(num_target_space_dims * num_orig_space_factor)},
+                {"n_quantized_integer_params": int(num_target_space_dims * num_orig_space_factor)},
+                {
+                    "n_quantized_continuous_params": int(
+                        num_target_space_dims * num_orig_space_factor
+                    )
+                },
                 # Mix of all three types
                 {
                     "n_continuous_params": int(num_target_space_dims * num_orig_space_factor / 3),