diff --git a/pandas/_libs/groupby.pyx b/pandas/_libs/groupby.pyx
index f0beab7193183..cc7c6e0e49c50 100644
--- a/pandas/_libs/groupby.pyx
+++ b/pandas/_libs/groupby.pyx
@@ -289,10 +289,8 @@ def group_cumprod(
 
                 if uses_mask:
                     isna_entry = mask[i, j]
-                elif int64float_t is float64_t or int64float_t is float32_t:
-                    isna_entry = val != val
                 else:
-                    isna_entry = False
+                    isna_entry = _treat_as_na(val, False)
 
                 if not isna_entry:
                     isna_prev = accum_mask[lab, j]
@@ -737,23 +735,10 @@ def group_sum(
                 for j in range(K):
                     val = values[i, j]
 
-                    # not nan
-                    # With dt64/td64 values, values have been cast to float64
-                    #  instead if int64 for group_sum, but the logic
-                    #  is otherwise the same as in _treat_as_na
                     if uses_mask:
                         isna_entry = mask[i, j]
-                    elif (
-                        sum_t is float32_t
-                        or sum_t is float64_t
-                        or sum_t is complex64_t
-                    ):
-                        # avoid warnings because of equality comparison
-                        isna_entry = not val == val
-                    elif sum_t is int64_t and is_datetimelike and val == NPY_NAT:
-                        isna_entry = True
                     else:
-                        isna_entry = False
+                        isna_entry = _treat_as_na(val, is_datetimelike)
 
                     if not isna_entry:
                         nobs[lab, j] += 1
@@ -831,10 +816,8 @@ def group_prod(
 
                 if uses_mask:
                     isna_entry = mask[i, j]
-                elif int64float_t is float32_t or int64float_t is float64_t:
-                    isna_entry = not val == val
                 else:
-                    isna_entry = False
+                    isna_entry = _treat_as_na(val, False)
 
                 if not isna_entry:
                     nobs[lab, j] += 1
@@ -906,7 +889,7 @@ def group_var(
                 if uses_mask:
                     isna_entry = mask[i, j]
                 else:
-                    isna_entry = not val == val
+                    isna_entry = _treat_as_na(val, False)
 
                 if not isna_entry:
                     nobs[lab, j] += 1
@@ -1008,9 +991,12 @@ def group_mean(
                 if uses_mask:
                     isna_entry = mask[i, j]
                 elif is_datetimelike:
+                    # With group_mean, we cannot just use _treat_as_na bc
+                    #  datetimelike dtypes get cast to float64 instead of
+                    #  to int64.
                     isna_entry = val == NPY_NAT
                 else:
-                    isna_entry = not val == val
+                    isna_entry = _treat_as_na(val, is_datetimelike)
 
                 if not isna_entry:
                     nobs[lab, j] += 1
@@ -1086,10 +1072,8 @@ def group_ohlc(
 
             if uses_mask:
                 isna_entry = mask[i, 0]
-            elif int64float_t is float32_t or int64float_t is float64_t:
-                isna_entry = val != val
             else:
-                isna_entry = False
+                isna_entry = _treat_as_na(val, False)
 
             if isna_entry:
                 continue
@@ -1231,15 +1215,26 @@ def group_quantile(
 # group_nth, group_last, group_rank
 # ----------------------------------------------------------------------
 
-cdef bint _treat_as_na(numeric_object_t val, bint is_datetimelike) nogil:
-    if numeric_object_t is object:
+ctypedef fused numeric_object_complex_t:
+    numeric_object_t
+    complex64_t
+    complex128_t
+
+
+cdef bint _treat_as_na(numeric_object_complex_t val, bint is_datetimelike) nogil:
+    if numeric_object_complex_t is object:
         # Should never be used, but we need to avoid the `val != val` below
         #  or else cython will raise about gil acquisition.
         raise NotImplementedError
 
-    elif numeric_object_t is int64_t:
+    elif numeric_object_complex_t is int64_t:
         return is_datetimelike and val == NPY_NAT
-    elif numeric_object_t is float32_t or numeric_object_t is float64_t:
+    elif (
+        numeric_object_complex_t is float32_t
+        or numeric_object_complex_t is float64_t
+        or numeric_object_complex_t is complex64_t
+        or numeric_object_complex_t is complex128_t
+    ):
         return val != val
     else:
         # non-datetimelike integer