diff --git a/CHANGELOG.md b/CHANGELOG.md
index 4761652ed6..46bd28bbe4 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,8 @@
 * loo-pit plot. The kde is computed over the data interval (this could be shorter than [0, 1]). The hdi is computed analitically (#1215)
 * Added `html_repr` of InferenceData objects for jupyter notebooks. (#1217)
 * Added support for PyJAGS via the function `from_pyjags` in the module arviz.data.io_pyjags. (#1219)
+* `from_pymc3` can now retrieve `coords` and `dims` from model context (#1228
+  and #1240)
 
 ### Maintenance and fixes
 * Include data from `MultiObservedRV` to `observed_data` when using
diff --git a/arviz/data/io_pymc3.py b/arviz/data/io_pymc3.py
index 98129a2fec..10a5657d78 100644
--- a/arviz/data/io_pymc3.py
+++ b/arviz/data/io_pymc3.py
@@ -148,12 +148,12 @@ def arbitrary_element(dct: Dict[Any, np.ndarray]) -> np.ndarray:
             self.ndraws = aelem.shape[0]
 
         self.coords = coords
-        if coords is None and hasattr(model, "coords"):
-            self.coords = model.coords
+        if coords is None and hasattr(self.model, "coords"):
+            self.coords = self.model.coords
 
         self.dims = dims
-        if dims is None and hasattr(model, "RV_dims"):
-            self.dims = {k: list(v) for k, v in model.RV_dims.items()}
+        if dims is None and hasattr(self.model, "RV_dims"):
+            self.dims = {k: list(v) for k, v in self.model.RV_dims.items()}
 
         self.observations, self.multi_observations = self.find_observations()
 
diff --git a/arviz/tests/external_tests/test_data_pymc.py b/arviz/tests/external_tests/test_data_pymc.py
index b90f82f575..41194a1ec8 100644
--- a/arviz/tests/external_tests/test_data_pymc.py
+++ b/arviz/tests/external_tests/test_data_pymc.py
@@ -202,7 +202,8 @@ def test_posterior_predictive_warning(self, data, eight_schools_params, caplog):
         packaging.version.Version(pm.__version__) < packaging.version.Version("3.9.0"),
         reason="Requires PyMC3 >= 3.9.0",
     )
-    def test_autodetect_coords_from_model(self):
+    @pytest.mark.parametrize("use_context", [True, False])
+    def test_autodetect_coords_from_model(self, use_context):
         df_data = pd.DataFrame(columns=["date"]).set_index("date")
         dates = pd.date_range(start="2020-05-01", end="2020-05-20")
         for city, mu in {"Berlin": 15, "San Marino": 18, "Paris": 16}.items():
@@ -231,8 +232,14 @@ def test_autodetect_coords_from_model(self):
                 draws=30,
                 step=pm.Metropolis(),
             )
-        idata = from_pymc3(trace=trace, model=model)
+            if use_context:
+                idata = from_pymc3(trace=trace)
+        if not use_context:
+            idata = from_pymc3(trace=trace, model=model)
 
+        assert "city" in list(idata.posterior.dims)
+        assert "city" in list(idata.observed_data.dims)
+        assert "date" in list(idata.observed_data.dims)
         np.testing.assert_array_equal(idata.posterior.coords["city"], coords["city"])
         np.testing.assert_array_equal(idata.observed_data.coords["date"], coords["date"])
         np.testing.assert_array_equal(idata.observed_data.coords["city"], coords["city"])