diff --git a/flox/aggregate_numbagg.py b/flox/aggregate_numbagg.py
index 507c6111b..f833f32d6 100644
--- a/flox/aggregate_numbagg.py
+++ b/flox/aggregate_numbagg.py
@@ -1,15 +1,27 @@
+from functools import partial
+
+import numbagg
+import numbagg.grouped
 import numpy as np
-from numbagg.grouped import group_nanmean, group_nansum
 
 
-def nansum_of_squares(
-    group_idx, array, *, axis=-1, func="sum", size=None, fill_value=None, dtype=None
+def _numbagg_wrapper(
+    group_idx,
+    array,
+    *,
+    axis=-1,
+    func="sum",
+    size=None,
+    fill_value=None,
+    dtype=None,
+    numbagg_func=None,
 ):
-    return group_nansum(
-        array**2,
+    return numbagg_func(
+        array,
         group_idx,
         axis=axis,
         num_labels=size,
+        # The following are unsupported
         # fill_value=fill_value,
         # dtype=dtype,
     )
@@ -18,7 +30,7 @@ def nansum_of_squares(
 def nansum(group_idx, array, *, axis=-1, size=None, fill_value=None, dtype=None):
     if np.issubdtype(array.dtype, np.bool_):
         array = array.astype(np.in64)
-    return group_nansum(
+    return numbagg.grouped.group_nansum(
         array,
         group_idx,
         axis=axis,
@@ -31,7 +43,7 @@ def nansum(group_idx, array, *, axis=-1, size=None, fill_value=None, dtype=None)
 def nanmean(group_idx, array, *, axis=-1, size=None, fill_value=None, dtype=None):
     if np.issubdtype(array.dtype, np.int_):
         array = array.astype(np.float64)
-    return group_nanmean(
+    return numbagg.grouped.group_nanmean(
         array,
         group_idx,
         axis=axis,
@@ -41,16 +53,13 @@ def nanmean(group_idx, array, *, axis=-1, size=None, fill_value=None, dtype=None
     )
 
 
-def nanlen(group_idx, array, *, axis=-1, size=None, fill_value=None, dtype=None):
-    return group_nansum(
-        (~np.isnan(array)).astype(int),
-        group_idx,
-        axis=axis,
-        num_labels=size,
-        # fill_value=fill_value,
-        # dtype=dtype,
-    )
-
+nansum_of_squares = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nansum_of_squares)
+nanlen = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_count)
+nanprod = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nanprod)
+nanfirst = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nanfirst)
+nanlast = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nanlast)
+nanargmax = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nanargmax)
+nanargmin = partial(_numbagg_wrapper, numbagg_func=numbagg.grouped.group_nanargmin)
 
 # sum = nansum
 # mean = nanmean