diff --git a/packages/openstef-core/src/openstef_core/types.py b/packages/openstef-core/src/openstef_core/types.py
index 1d536f9cb..2bd452bdd 100644
--- a/packages/openstef-core/src/openstef_core/types.py
+++ b/packages/openstef-core/src/openstef_core/types.py
@@ -338,7 +338,11 @@ def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHa
         Returns:
             Core schema for Pydantic validation.
         """
-        return core_schema.no_info_after_validator_function(cls, handler(float))
+        return core_schema.no_info_after_validator_function(
+            cls,
+            handler(float),
+            serialization=core_schema.plain_serializer_function_ser_schema(float),
+        )
 
     def format(self) -> str:
         """Instance method to format the quantile as a string.
diff --git a/packages/openstef-core/tests/unit/test_types.py b/packages/openstef-core/tests/unit/test_types.py
index 189c02733..1eb166929 100644
--- a/packages/openstef-core/tests/unit/test_types.py
+++ b/packages/openstef-core/tests/unit/test_types.py
@@ -2,13 +2,15 @@
 #
 # SPDX-License-Identifier: MPL-2.0
 
+import warnings
 from datetime import UTC, datetime, time, timedelta, timezone
 
 import pandas as pd
 import pytest
 import pytz
+from pydantic import BaseModel
 
-from openstef_core.types import AvailableAt, LeadTime
+from openstef_core.types import AvailableAt, LeadTime, Quantile, QuantileOrGlobal
 
 
 @pytest.mark.parametrize(
@@ -342,3 +344,20 @@ def test_available_at_apply_index_matches_apply():
     scalar = pd.DatetimeIndex([at.apply(ts.to_pydatetime()) for ts in index])
 
     pd.testing.assert_index_equal(vectorized, scalar)
+
+
+def test_quantile_serialization_no_warnings():
+    """Quantile used as dict key in a QuantileOrGlobal union must not trigger pydantic serialization warnings."""
+
+    class Model(BaseModel):
+        metrics: dict[QuantileOrGlobal, dict[str, float]]
+
+    m = Model(metrics={Quantile(0.05): {"mae": 1.0}, Quantile(0.5): {"mae": 2.0}, "global": {"mae": 1.5}})
+
+    with warnings.catch_warnings():
+        warnings.filterwarnings("error", category=UserWarning, message="Pydantic serializer")
+        data = m.model_dump_json()
+
+    assert '"0.05"' in data
+    assert '"0.5"' in data
+    assert '"global"' in data