diff --git a/numpyro/infer/elbo.py b/numpyro/infer/elbo.py
index 3c4bbb8cf..b29cbd45e 100644
--- a/numpyro/infer/elbo.py
+++ b/numpyro/infer/elbo.py
@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from collections import OrderedDict, defaultdict
-from functools import partial
+from functools import partial, reduce
 from operator import itemgetter
 import warnings
 
@@ -959,6 +959,19 @@ def single_particle_elbo(rng_key):
                         *(frozenset(f.inputs) & group_plates for f in group_factors)
                     )
                     elim_plates = group_plates - outermost_plates
+                    plate_to_scale = {}
+                    for name in group_names:
+                        for plate, value in (
+                            model_trace[name].get("plate_to_scale", {}).items()
+                        ):
+                            if plate in plate_to_scale:
+                                if value != plate_to_scale[plate]:
+                                    raise ValueError(
+                                        "Expected all enumerated sample sites to share a common scale factor, "
+                                        f"but found different scales at plate('{plate}')."
+                                    )
+                            else:
+                                plate_to_scale[plate] = value
                     with funsor.interpretations.normalize:
                         cost = funsor.sum_product.sum_product(
                             funsor.ops.logaddexp,
@@ -966,26 +979,20 @@ def single_particle_elbo(rng_key):
                             group_factors,
                             plates=group_plates,
                             eliminate=group_sum_vars | elim_plates,
+                            plate_to_scale=plate_to_scale,
                         )
                     # TODO: add memoization
                     cost = funsor.optimizer.apply_optimizer(cost)
                     # incorporate the effects of subsampling and handlers.scale through a common scale factor
-                    scales_set = set()
-                    for name in group_names | group_sum_vars:
-                        site_scale = model_trace[name]["scale"]
-                        if site_scale is None:
-                            site_scale = 1.0
-                        if isinstance(site_scale, jnp.ndarray):
-                            raise ValueError(
-                                "Enumeration only supports scalar handlers.scale"
-                            )
-                        scales_set.add(float(site_scale))
-                    if len(scales_set) != 1:
-                        raise ValueError(
-                            "Expected all enumerated sample sites to share a common scale, "
-                            f"but found {len(scales_set)} different scales."
-                        )
-                    scale = next(iter(scales_set))
+                    scale = reduce(
+                        funsor.ops.mul,
+                        [
+                            value
+                            for plate, value in plate_to_scale.items()
+                            if plate not in elim_plates
+                        ],
+                        1.0,
+                    )
                     # combine deps
                     deps = frozenset().union(
                         *[model_deps[name] for name in group_names]
diff --git a/setup.py b/setup.py
index bba87d335..334905d17 100644
--- a/setup.py
+++ b/setup.py
@@ -61,7 +61,7 @@
         "dev": [
             "dm-haiku",
             "flax",
-            "funsor>=0.4.1",
+            "funsor>=0.4.6",
             "graphviz",
             "jaxns>=2.0.1",
             "matplotlib",
diff --git a/test/contrib/test_enum_elbo.py b/test/contrib/test_enum_elbo.py
index d464fb33a..2d166cce7 100644
--- a/test/contrib/test_enum_elbo.py
+++ b/test/contrib/test_enum_elbo.py
@@ -2314,14 +2314,10 @@ def actual_loss_fn(params_raw):
         }
         return elbo.loss(random.PRNGKey(0), {}, model_subsample, guide, params)
 
-    with pytest.raises(
-        ValueError, match="Expected all enumerated sample sites to share a common scale"
-    ):
-        # This never gets run because we don't support this yet.
-        actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
+    actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
 
-        assert_equal(actual_loss, expected_loss, prec=1e-5)
-        assert_equal(actual_grads, expected_grads, prec=1e-5)
+    assert_equal(actual_loss, expected_loss, prec=1e-5)
+    assert_equal(actual_grads, expected_grads, prec=1e-5)
 
 
 @pytest.mark.parametrize("scale", [1, 10])
@@ -2389,20 +2385,16 @@ def actual_loss_fn(params_raw):
         }
         return elbo.loss(random.PRNGKey(0), {}, model_subsample, guide, params)
 
-    with pytest.raises(
-        ValueError, match="Expected all enumerated sample sites to share a common scale"
-    ):
-        # This never gets run because we don't support this yet.
-        actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
+    actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
 
-        assert_equal(actual_loss, expected_loss, prec=1e-5)
-        assert_equal(actual_grads, expected_grads, prec=1e-5)
+    assert_equal(actual_loss, expected_loss, prec=1e-5)
+    assert_equal(actual_grads, expected_grads, prec=1e-5)
 
 
 @pytest.mark.parametrize("scale", [1, 10])
 def test_model_enum_subsample_3(scale):
     # Enumerate: a
-    # Subsample: a, b, c
+    # Subsample: b, c
     # [ a - [----> b    ]
     # [  \  [           ]
     # [   - [- [-> c  ] ]
@@ -2464,14 +2456,10 @@ def actual_loss_fn(params_raw):
         }
         return elbo.loss(random.PRNGKey(0), {}, model_subsample, guide, params)
 
-    with pytest.raises(
-        ValueError, match="Expected all enumerated sample sites to share a common scale"
-    ):
-        # This never gets run because we don't support this yet.
-        actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
+    actual_loss, actual_grads = jax.value_and_grad(actual_loss_fn)(params_raw)
 
-        assert_equal(actual_loss, expected_loss, prec=1e-3)
-        assert_equal(actual_grads, expected_grads, prec=1e-5)
+    assert_equal(actual_loss, expected_loss, prec=1e-3)
+    assert_equal(actual_grads, expected_grads, prec=1e-5)
 
 
 def test_guide_plate_contraction():