diff --git a/backends/webgpu/test/op_tests/cases.py b/backends/webgpu/test/op_tests/cases.py
index f23e2120463..d001b5857f4 100644
--- a/backends/webgpu/test/op_tests/cases.py
+++ b/backends/webgpu/test/op_tests/cases.py
@@ -418,7 +418,11 @@ def _linear_fp32_suite() -> WebGPUTestSuite:
 @register_op_test("conv2d")
 def _conv2d_suite() -> WebGPUTestSuite:
     # DaViT patch-embed / downsample convs + conv_transpose2d (same registration,
-    # folded by the `transposed` arg). NCHW fp32.
+    # folded by the `transposed` arg). NCHW fp32. Routing coverage (all vs the
+    # same fp64 golden): patch_embed/conv3x3_pad1/strided/gemm_batched are
+    # groups==1 → im2col tiled GEMM (gemm_batched pins the B>1 output write);
+    # grouped_vec4 (groups=2, icpg=4) → direct vec4 kernel; depthwise (groups=8,
+    # icpg=1) → direct scalar; transpose2x → conv_transpose2d.
     return WebGPUTestSuite(
         module_factory=make_conv,
         cases=[
@@ -454,6 +458,22 @@ def _conv2d_suite() -> WebGPUTestSuite:
                 },
                 inputs=(InputSpec(shape=(1, 8, 8, 8), gen=_chw_ramp),),
             ),
+            Case(
+                name="grouped_vec4",
+                construct={
+                    "in_ch": 8,
+                    "out_ch": 8,
+                    "kernel": 3,
+                    "padding": 1,
+                    "groups": 2,
+                },
+                inputs=(InputSpec(shape=(1, 8, 8, 8), gen=_chw_ramp),),
+            ),
+            Case(
+                name="gemm_batched",
+                construct={"in_ch": 8, "out_ch": 16, "kernel": 3, "padding": 1},
+                inputs=(InputSpec(shape=(2, 8, 16, 16), gen=_chw_ramp),),
+            ),
             Case(
                 name="transpose2x",
                 construct={