diff --git a/vllm/config.py b/vllm/config.py
index 8a839bb6e5ce..d99971670ab7 100644
--- a/vllm/config.py
+++ b/vllm/config.py
@@ -3450,6 +3450,10 @@ def __post_init__(self):
             # FIXME(woosuk): Disable inductor to reduce the compilation time
             # and avoid any potential issues with the inductor.
             self.compilation_config.custom_ops = ["none"]
+            if current_platform.is_rocm():
+                self.compilation_config.custom_ops = [
+                    "+rms_norm", "+silu_and_mul"
+                ]
             self.compilation_config.use_cudagraph = True
             self.compilation_config.use_inductor = True
             self.compilation_config.cudagraph_num_of_warmups = 1
diff --git a/vllm/model_executor/layers/tuned_gemm.py b/vllm/model_executor/layers/tuned_gemm.py
index ce3ab80985bd..2f26bf5c365b 100644
--- a/vllm/model_executor/layers/tuned_gemm.py
+++ b/vllm/model_executor/layers/tuned_gemm.py
@@ -8,6 +8,7 @@
 import torch.nn.functional as F
 
 from vllm import _custom_ops as ops
+from vllm import envs
 from vllm.envs import VLLM_USE_ROCM_SKINNY_GEMM
 from vllm.platforms import current_platform
 from vllm.utils import is_mi250, is_navi
@@ -68,6 +69,8 @@ def create_ds(self):
         self.solids = solds
 
     def query_sol(self, m, n, k, bias, dtype):
+        if envs.VLLM_USE_V1:
+            return 0, 0
         return self.solids.get((m, n, k, bias, str(dtype)), (0, 0))
 
     def apply_skinny(self, m, n, k, inp_view, weights):
diff --git a/vllm/v1/attention/backends/rocm_attn.py b/vllm/v1/attention/backends/rocm_attn.py
index 640c3b3d4fbb..28093646e9fb 100644
--- a/vllm/v1/attention/backends/rocm_attn.py
+++ b/vllm/v1/attention/backends/rocm_attn.py
@@ -110,6 +110,7 @@ def forward(
         value: torch.Tensor,
         kv_cache: torch.Tensor,
         attn_metadata: FlashAttentionMetadata,
+        fp8_out_scale: Optional[torch.Tensor],
         output: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
         """Forward pass with FlashAttention.