diff --git a/docs/sphinx/source/whatsnew/v0.16.0.rst b/docs/sphinx/source/whatsnew/v0.16.0.rst
index 67863eb9e5..6d62b9e1c6 100644
--- a/docs/sphinx/source/whatsnew/v0.16.0.rst
+++ b/docs/sphinx/source/whatsnew/v0.16.0.rst
@@ -2,10 +2,12 @@
 
 
 v0.16.0
------------------------
-
 Breaking Changes
 ~~~~~~~~~~~~~~~~
+* Change output type of :py:func:`pvlib.irradiance.perez` and
+  :py:func:`pvlib.irradiance.perez_driesse` from ``OrderedDict`` to ``dict`` when
+  ``return_components=True`` to be consistent with other models.
+  (:pull:`2789`)
 * Remove empty ``poa_horizon`` key from the ``diffuse_components`` output of
   :py:func:`pvlib.irradiance.haydavies`.
   (:pull:`2788`)
@@ -45,4 +47,4 @@ Maintenance
 
 Contributors
 ~~~~~~~~~~~~
-
+* Carolina Crespo (:ghuser:`cbcrespo`)
diff --git a/pvlib/irradiance.py b/pvlib/irradiance.py
index 048d8aa461..98bd948286 100644
--- a/pvlib/irradiance.py
+++ b/pvlib/irradiance.py
@@ -1104,7 +1104,7 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
 
     Returns
     --------
-    numeric, OrderedDict, or DataFrame
+    numeric, dict, or DataFrame
         Return type controlled by `return_components` argument.
         If ``return_components=False``, `sky_diffuse` is returned.
         If ``return_components=True``, `diffuse_components` is returned.
@@ -1113,7 +1113,7 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
         The sky diffuse component of the solar radiation on a tilted
         surface.
 
-    diffuse_components : OrderedDict (array input) or DataFrame (Series input)
+    diffuse_components : dict (array input) or DataFrame (Series input)
         Keys/columns are:
             * poa_sky_diffuse: Total sky diffuse
             * poa_isotropic
@@ -1200,13 +1200,12 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
         sky_diffuse = np.where(np.isnan(airmass), 0, sky_diffuse)
 
     if return_components:
-        diffuse_components = OrderedDict()
-        diffuse_components['poa_sky_diffuse'] = sky_diffuse
-
-        # Calculate the different components
-        diffuse_components['poa_isotropic'] = dhi * term1
-        diffuse_components['poa_circumsolar'] = dhi * term2
-        diffuse_components['poa_horizon'] = dhi * term3
+        diffuse_components = {
+            'poa_sky_diffuse': sky_diffuse,
+            'poa_isotropic': dhi * term1,
+            'poa_circumsolar': dhi * term2,
+            'poa_horizon': dhi * term3
+        }
 
         # Set values of components to 0 when sky_diffuse is 0
         mask = sky_diffuse == 0
@@ -1346,7 +1345,7 @@ def perez_driesse(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
 
     Returns
     --------
-    numeric, OrderedDict, or DataFrame
+    numeric, dict, or DataFrame
         Return type controlled by `return_components` argument.
         If ``return_components=False``, `sky_diffuse` is returned.
         If ``return_components=True``, `diffuse_components` is returned.
@@ -1355,7 +1354,7 @@ def perez_driesse(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
         The sky diffuse component of the solar radiation on a tilted
         surface.
 
-    diffuse_components : OrderedDict (array input) or DataFrame (Series input)
+    diffuse_components : dict (array input) or DataFrame (Series input)
         Keys/columns are:
             * poa_sky_diffuse: Total sky diffuse
             * poa_isotropic
@@ -1420,13 +1419,12 @@ def perez_driesse(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
     sky_diffuse = np.maximum(dhi * (term1 + term2 + term3), 0)
 
     if return_components:
-        diffuse_components = OrderedDict()
-        diffuse_components['poa_sky_diffuse'] = sky_diffuse
-
-        # Calculate the different components
-        diffuse_components['poa_isotropic'] = dhi * term1
-        diffuse_components['poa_circumsolar'] = dhi * term2
-        diffuse_components['poa_horizon'] = dhi * term3
+        diffuse_components = {
+            'poa_sky_diffuse': sky_diffuse,
+            'poa_isotropic': dhi * term1,
+            'poa_circumsolar': dhi * term2,
+            'poa_horizon': dhi * term3
+        }
 
         if isinstance(sky_diffuse, pd.Series):
             diffuse_components = pd.DataFrame(diffuse_components)