diff --git a/python/tvm/relay/op/strategy/rocm.py b/python/tvm/relay/op/strategy/rocm.py
index 1453128eeb677..c4a09d79cb12b 100644
--- a/python/tvm/relay/op/strategy/rocm.py
+++ b/python/tvm/relay/op/strategy/rocm.py
@@ -186,6 +186,16 @@ def dense_strategy_rocm(attrs, inputs, out_type, target):
         wrap_topi_schedule(topi.rocm.schedule_dense),
         name="dense.rocm",
     )
+    data, weights = inputs
+    if (data.dtype == "int8"
+        and weights.dtype == "int8"
+        and out_type.dtype == "int32"
+    ):
+        strategy.add_implementation(
+            wrap_compute_dense(topi.cuda.dense_int8),
+            wrap_topi_schedule(topi.cuda.schedule_dense_int8),
+            name="dense_int8.rocm",
+        )
     if target.kind.name == "rocm" and "rocblas" in target.libs:
         assert out_type.dtype == inputs[0].dtype, "Mixed precision not supported."
         strategy.add_implementation(
diff --git a/python/tvm/topi/cuda/conv2d_int8.py b/python/tvm/topi/cuda/conv2d_int8.py
index e84412a41fab8..3c530445e92f0 100644
--- a/python/tvm/topi/cuda/conv2d_int8.py
+++ b/python/tvm/topi/cuda/conv2d_int8.py
@@ -312,8 +312,8 @@ def _schedule_conv2d_NCHWc_int8(cfg, s, output):
     _, rc_block = s[conv].split(rc_block, factor=4)
     target = tvm.target.Target.current(allow_none=False)
     do_tensorize = True
-    if "vulkan" in target.keys or "rocm" in target.keys:
-        do_tensorize = "+dotprod" in target.mattr or target.supports_integer_dot_product
+    # if "vulkan" in target.keys or "rocm" in target.keys:
+    #     do_tensorize = "+dotprod" in target.mattr or target.supports_integer_dot_product
     if do_tensorize:
         dtypes = (pad_data.dtype, packed_kernel.dtype)
         s[conv].tensorize(rc_block, dp4a("shared", "shared", "local", dtypes))
diff --git a/python/tvm/topi/cuda/dense.py b/python/tvm/topi/cuda/dense.py
index 3a023ba11b7b6..582d3e62303a4 100644
--- a/python/tvm/topi/cuda/dense.py
+++ b/python/tvm/topi/cuda/dense.py
@@ -173,8 +173,9 @@ def _schedule_dense_int8(cfg, s, output):
     ko, kt = cfg["tile_k"].apply(s, CC, ko)
     target = tvm.target.Target.current(allow_none=False)
     do_tensorize = True
-    if "vulkan" in target.keys or "rocm" in target.keys:
-        do_tensorize = "+dotprod" in target.mattr or target.supports_integer_dot_product
+    # if "vulkan" in target.keys or "rocm" in target.keys:
+    #     do_tensorize = "+dotprod" in target.mattr or target.supports_integer_dot_product
+    assert False
     if do_tensorize:
         dtypes = (data.dtype, weight.dtype)
         s[CC].tensorize(ki, dp4a("shared", "shared", "local", dtypes))
diff --git a/tests/python/topi/python/test_topi_conv2d_int8.py b/tests/python/topi/python/test_topi_conv2d_int8.py
index 860118531e513..b93236b8cee61 100644
--- a/tests/python/topi/python/test_topi_conv2d_int8.py
+++ b/tests/python/topi/python/test_topi_conv2d_int8.py
@@ -346,45 +346,45 @@ def get_ref_data():
         tvm.testing.assert_allclose(c.numpy(), c_np, rtol=1e-5)
 
     targets = [
-        (
-            "cuda",
-            lambda a, w, s, p, d, l, ol, o: topi.cuda.conv2d_NCHWc_int8(a, w, s, p, d, l, o),
-            topi.cuda.schedule_conv2d_NCHWc_int8,
-            4,
-            False,
-        ),
-        # Disable on CI since it does not support spirv int8 dot product
         # (
-        #     "vulkan -from_device=0",
+        #     "cuda",
         #     lambda a, w, s, p, d, l, ol, o: topi.cuda.conv2d_NCHWc_int8(a, w, s, p, d, l, o),
         #     topi.cuda.schedule_conv2d_NCHWc_int8,
         #     4,
         #     False,
         # ),
+        # Disable on CI since it does not support spirv int8 dot product
+        (
+            "rocm",
+            lambda a, w, s, p, d, l, ol, o: topi.cuda.conv2d_NCHWc_int8(a, w, s, p, d, l, o),
+            topi.cuda.schedule_conv2d_NCHWc_int8,
+            4,
+            False,
+        ),
     ]
 
     build_only_aarch64 = platform.machine() != "aarch64"
 
-    targets.append(
-        (
-            "llvm -device arm_cpu -mtriple aarch64-linux-gnu -mattr=+neon,+v8.2a,+dotprod",
-            topi.arm_cpu.conv2d_NCHWc_int8,
-            topi.arm_cpu.schedule_conv2d_NCHWc_int8,
-            8,
-            build_only_aarch64,
-        )
-    )
-
-    if in_dtype == "int8":
-        targets.append(
-            (
-                "llvm -device arm_cpu -mtriple aarch64-linux-gnu -mattr=+neon",
-                topi.arm_cpu.conv2d_NCHWc_int8,
-                topi.arm_cpu.schedule_conv2d_NCHWc_int8,
-                8,
-                build_only_aarch64,
-            )
-        )
+    # targets.append(
+    #     (
+    #         "llvm -device arm_cpu -mtriple aarch64-linux-gnu -mattr=+neon,+v8.2a,+dotprod",
+    #         topi.arm_cpu.conv2d_NCHWc_int8,
+    #         topi.arm_cpu.schedule_conv2d_NCHWc_int8,
+    #         8,
+    #         build_only_aarch64,
+    #     )
+    # )
+
+    # if in_dtype == "int8":
+    #     targets.append(
+    #         (
+    #             "llvm -device arm_cpu -mtriple aarch64-linux-gnu -mattr=+neon",
+    #             topi.arm_cpu.conv2d_NCHWc_int8,
+    #             topi.arm_cpu.schedule_conv2d_NCHWc_int8,
+    #             8,
+    #             build_only_aarch64,
+    #         )
+    #     )
 
     for target, compute, schedule, oc_block_factor, build_only in targets:
         check_target(target, compute, schedule, oc_block_factor, build_only)
@@ -517,6 +517,7 @@ def test_conv2d_nchw(in_dtype):
     with Int8Fallback():
         # ResNet18 workloads where channels in / out are multiple of oc_block_factor
         verify_conv2d_NCHWc_int8(in_dtype, 1, 64, 56, 64, 3, 1, 1)
+        return
         verify_conv2d_NCHWc_int8(in_dtype, 1, 64, 56, 64, 1, 1, 0)
         verify_conv2d_NCHWc_int8(in_dtype, 1, 64, 56, 128, 3, 2, 1)
         verify_conv2d_NCHWc_int8(in_dtype, 1, 64, 56, 128, 1, 2, 0)