diff --git a/test/inductor/test_flex_decoding.py b/test/inductor/test_flex_decoding.py
index 46acd0c1cdca3..dfd6dce40b999 100644
--- a/test/inductor/test_flex_decoding.py
+++ b/test/inductor/test_flex_decoding.py
@@ -22,7 +22,10 @@
 )
 from torch.testing import FileCheck
 from torch.testing._internal import common_utils
-from torch.testing._internal.common_cuda import PLATFORM_SUPPORTS_BF16
+from torch.testing._internal.common_cuda import (
+    PLATFORM_SUPPORTS_BF16,
+    PLATFORM_SUPPORTS_FLASH_ATTENTION,
+)
 from torch.testing._internal.common_device_type import (
     flex_attention_supported_platform as supported_platform,
     instantiate_device_type_tests,
@@ -1582,6 +1585,7 @@ def mask_mod(b, h, q, kv):
         self.assertEqual(out[:, :, M:, :].sum(), 0)
 
     @supported_platform
+    @unittest.skipIf(not PLATFORM_SUPPORTS_FLASH_ATTENTION, "Some archs don't support SDPA")
     def test_windowed_no_mask_vs_sdpa(self, device):
         score_mod = _generate_windowed(1000)
         attention = functools.partial(flex_attention, score_mod=score_mod)
diff --git a/test/inductor/test_max_autotune.py b/test/inductor/test_max_autotune.py
index d1c5637d82008..eba9fbaf131c5 100644
--- a/test/inductor/test_max_autotune.py
+++ b/test/inductor/test_max_autotune.py
@@ -37,11 +37,15 @@
 )
 from torch._inductor.template_heuristics import CUDAConfigHeuristic, GemmConfig
 from torch.testing._internal.common_cuda import PLATFORM_SUPPORTS_FP8
+from torch.testing._internal.common_device_type import largeTensorTest
 from torch.testing._internal.common_utils import (
     instantiate_parametrized_tests,
     IS_WINDOWS,
     parametrize,
     TEST_WITH_ROCM,
+    MI300_ARCH,
+    runOnRocmArch,
+    skipIfXpu,
 )
 from torch.testing._internal.logging_utils import multiple_logs_to_string
 from torch.utils._triton import has_triton_tma_device
@@ -54,7 +58,6 @@
 from torch._inductor.virtualized import V
 from torch.fx.experimental.proxy_tensor import make_fx
 from torch.testing import FileCheck
-from torch.testing._internal.common_utils import MI300_ARCH, runOnRocmArch, skipIfXpu
 from torch.testing._internal.inductor_utils import (
     get_func_call,
     get_kernel_launch,
@@ -804,6 +807,8 @@ def test_conv_backend(self):
 
         self.assertIn("NoValidChoicesError", str(context.exception))
 
+    # Some ROCm GPUs don't have enough VRAM to run all autotune configurations and padding benchmarks
+    @largeTensorTest("30 GB", device=GPU_TYPE)
     def test_non_contiguous_input_mm(self):
         """
         Make sure the triton template can work with non-contiguous inputs without crash.
@@ -856,6 +861,8 @@ def f(x, y):
     # TODO: fix accuracy failure of the triton template on XPU.
     # and enable this test case.
     @skipIfXpu
+    # Some ROCm GPUs don't have enough VRAM to run all autotune configurations and padding benchmarks
+    @largeTensorTest("30 GB", device=GPU_TYPE)
     def test_non_contiguous_input_mm_plus_mm(self):
         x1 = rand_strided((50257, 32768), (1, 50304), device=GPU_TYPE)
         y1 = rand_strided((32768, 768), (768, 1), device=GPU_TYPE)