diff --git a/tests/compile/test_dynamic_shapes_compilation.py b/tests/compile/test_dynamic_shapes_compilation.py
index bbd62237c5..1775b2c9de 100644
--- a/tests/compile/test_dynamic_shapes_compilation.py
+++ b/tests/compile/test_dynamic_shapes_compilation.py
@@ -222,3 +222,47 @@ def test_model_specialization_with_evaluate_guards(
         torch.randn(1, 10).cuda(),
         is_01_specialization=True,
     )
+
+
+@pytest.mark.skipif(not is_torch_equal_or_newer("2.10.0"), reason="requires torch 2.10")
+def test_piecewise_backend_empty_sym_shape_indices():
+    """Test that PiecewiseBackend handles empty sym_shape_indices correctly.
+
+    When all inputs have static shapes (no torch.SymInt), sym_shape_indices
+    will be empty. The fix in PiecewiseBackend.__call__ handles this case
+    by using the first compiled range_entry.
+    """
+    gc.collect()
+    torch.accelerator.empty_cache()
+    torch.accelerator.synchronize()
+
+    # Use small max_model_len and max_num_batched_tokens to encourage
+    # static shape compilation with empty sym_shape_indices
+    llm = LLM(
+        model="Qwen/Qwen3-0.6B",
+        max_model_len=512,
+        max_num_batched_tokens=1,
+        compilation_config={
+            "mode": CompilationMode.VLLM_COMPILE,
+            "dynamic_shapes_config": {
+                "type": DynamicShapesType.BACKED.value,
+            },
+        },
+    )
+
+    sampling_params = SamplingParams(temperature=0, top_p=0.95, max_tokens=10)
+
+    # Generate with static shape inputs
+    output = llm.generate("Hello, my name is", sampling_params=sampling_params)
+    result = output[0].outputs[0].text
+    assert len(result) > 0, "Should generate non-empty output"
+
+    # Generate again to verify compilation works with empty sym_shape_indices
+    output = llm.generate("The capital of France is", sampling_params=sampling_params)
+    result = output[0].outputs[0].text
+    assert len(result) > 0, "Should generate non-empty output on second run"
+
+    del llm
+    gc.collect()
+    torch.accelerator.empty_cache()
+    torch.accelerator.synchronize()
diff --git a/vllm/compilation/piecewise_backend.py b/vllm/compilation/piecewise_backend.py
index e167a303de..02a4dad546 100644
--- a/vllm/compilation/piecewise_backend.py
+++ b/vllm/compilation/piecewise_backend.py
@@ -354,12 +354,22 @@ class PiecewiseBackend:
         return None
 
     def __call__(self, *args: Any) -> Any:
-        runtime_shape = args[self.sym_shape_indices[0]]
-        range_entry = self._find_range_for_shape(runtime_shape)
+        if self.sym_shape_indices:
+            runtime_shape = args[self.sym_shape_indices[0]]
+            range_entry = self._find_range_for_shape(runtime_shape)
+            assert range_entry is not None, (
+                f"Shape: {runtime_shape} out of considered ranges: "
+                f"{self.compile_ranges}"
+            )
+        else:
+            # All inputs have static shapes; use the only compiled range_entry
+            compiled_entries = [re for re in self.range_entries.values() if re.compiled]
+            assert len(compiled_entries) == 1, (
+                f"Expected exactly one compiled range_entry for static shape "
+                f"compilation, but found {len(compiled_entries)}"
+            )
+            range_entry = compiled_entries[0]
 
-        assert range_entry is not None, (
-            f"Shape: {runtime_shape} out of considered ranges: {self.compile_ranges}"
-        )
         assert range_entry.compiled, (
             "All ranges should be compiled or loaded up front in "
             "PiecewiseBackend.__init__. "