diff --git a/python-package/xgboost/core.py b/python-package/xgboost/core.py
index 76251d65c522..118b0013d3d8 100644
--- a/python-package/xgboost/core.py
+++ b/python-package/xgboost/core.py
@@ -2488,6 +2488,7 @@ def inplace_predict(
             _arrow_transform,
             _is_arrow,
             _is_cudf_df,
+            _is_cudf_pandas,
             _is_cupy_alike,
             _is_list,
             _is_np_array_like,
@@ -2497,6 +2498,9 @@ def inplace_predict(
             _transform_pandas_df,
         )
 
+        if _is_cudf_pandas(data):
+            data = data._fsproxy_fast  # pylint: disable=protected-access
+
         enable_categorical = True
         if _is_arrow(data):
             data = _arrow_transform(data)
diff --git a/python-package/xgboost/data.py b/python-package/xgboost/data.py
index bd196e2e59f9..3556b486d595 100644
--- a/python-package/xgboost/data.py
+++ b/python-package/xgboost/data.py
@@ -835,6 +835,16 @@ def _is_cudf_df(data: DataType) -> bool:
     return lazy_isinstance(data, "cudf.core.dataframe", "DataFrame")
 
 
+def _is_cudf_pandas(data: DataType) -> bool:
+    """Must go before both pandas and cudf checks."""
+    return (
+        lazy_isinstance(data, "pandas.core.frame", "DataFrame")
+        or lazy_isinstance(data, "pandas.core.series", "Series")
+    ) and lazy_isinstance(
+        type(data), "cudf.pandas.fast_slow_proxy", "_FastSlowProxyMeta"
+    )
+
+
 def _get_cudf_cat_predicate() -> Callable[[Any], bool]:
     try:
         from cudf import CategoricalDtype
@@ -1187,6 +1197,8 @@ def dispatch_data_backend(
         )
     if _is_arrow(data):
         data = _arrow_transform(data)
+    if _is_cudf_pandas(data):
+        data = data._fsproxy_fast  # pylint: disable=protected-access
     if _is_pandas_series(data):
         import pandas as pd
 
@@ -1327,6 +1339,8 @@ def dispatch_meta_backend(
         return
     if _is_arrow(data):
         data = _arrow_transform(data)
+    if _is_cudf_pandas(data):
+        data = data._fsproxy_fast  # pylint: disable=protected-access
     if _is_pandas_df(data):
         _meta_from_pandas_df(data, name, dtype=dtype, handle=handle)
         return
@@ -1398,6 +1412,8 @@ def _proxy_transform(
     feature_types: Optional[FeatureTypes],
     enable_categorical: bool,
 ) -> TransformedData:
+    if _is_cudf_pandas(data):
+        data = data._fsproxy_fast  # pylint: disable=protected-access
     if _is_cudf_df(data) or _is_cudf_ser(data):
         return _transform_cudf_df(
             data, feature_names, feature_types, enable_categorical