diff --git a/vllm/attention/ops/triton_flash_attention.py b/vllm/attention/ops/triton_flash_attention.py
index 3d53cd4b5700f..a49df831b46ea 100644
--- a/vllm/attention/ops/triton_flash_attention.py
+++ b/vllm/attention/ops/triton_flash_attention.py
@@ -24,6 +24,8 @@
 import triton
 import triton.language as tl
 
+from vllm.utils import is_navi
+
 torch_dtype: tl.constexpr = torch.float16
 
 
@@ -217,88 +219,80 @@ def _attn_fwd_inner(
     return acc, l_i, m_i
 
 
-@triton.autotune(
-    configs=[
+def get_cdna_autotune_configs():
+    return [
         triton.Config(
             {
-                "BLOCK_M": 256,
-                "BLOCK_N": 64,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 256,
+                'BLOCK_N': 64,
+                'waves_per_eu': 2,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=8,
-        ),
+            num_warps=8),
         triton.Config(
             {
-                "BLOCK_M": 128,
-                "BLOCK_N": 128,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 128,
+                'BLOCK_N': 128,
+                'waves_per_eu': 2,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=4,
-        ),
+            num_warps=4),
         triton.Config(
             {
-                "BLOCK_M": 256,
-                "BLOCK_N": 128,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 256,
+                'BLOCK_N': 128,
+                'waves_per_eu': 2,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=8,
-        ),
+            num_warps=8),
         triton.Config(
             {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 1,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 128,
+                'BLOCK_N': 64,
+                'waves_per_eu': 1,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=4,
-        ),
+            num_warps=4),
         triton.Config(
             {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 3,
-                "PRE_LOAD_V": True,
+                'BLOCK_M': 128,
+                'BLOCK_N': 64,
+                'waves_per_eu': 3,
+                'PRE_LOAD_V': True
             },
             num_stages=1,
-            num_warps=4,
-        ),
+            num_warps=4),
         triton.Config(
             {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 3,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 128,
+                'BLOCK_N': 64,
+                'waves_per_eu': 3,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=4,
-        ),
+            num_warps=4),
         triton.Config(
             {
-                "BLOCK_M": 64,
-                "BLOCK_N": 64,
-                "waves_per_eu": 4,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 64,
+                'BLOCK_N': 64,
+                'waves_per_eu': 4,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=8,
-        ),
+            num_warps=8),
         triton.Config(
             {
-                "BLOCK_M": 32,
-                "BLOCK_N": 32,
-                "waves_per_eu": 4,
-                "PRE_LOAD_V": False,
+                'BLOCK_M': 32,
+                'BLOCK_N': 32,
+                'waves_per_eu': 4,
+                'PRE_LOAD_V': False
             },
             num_stages=1,
-            num_warps=8,
-        ),
+            num_warps=8),
         # TODO: This config fails with head_size not pow2 with data mismatches.
         #    triton.Config({'BLOCK_M': 32, 'BLOCK_N': 16, 'waves_per_eu': 1,
         #                   'PRE_LOAD_V': False}, num_stages=1, num_warps=4),
@@ -314,8 +308,93 @@ def _attn_fwd_inner(
         #     num_stages=1,
         #     num_warps=4,
         # ),
-    ],
-    key=['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL', 'USE_FP8'],
+    ], ['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL', 'USE_FP8']
+
+
+def get_rdna_autotune_configs():
+    return [
+        triton.Config(
+            {
+                'BLOCK_M': 32,
+                'BLOCK_N': 32,
+                'waves_per_eu': 4,
+                'PRE_LOAD_V': False
+            },
+            num_stages=1,
+            num_warps=2),
+        triton.Config(
+            {
+                'BLOCK_M': 32,
+                'BLOCK_N': 32,
+                'waves_per_eu': 2,
+                'PRE_LOAD_V': False
+            },
+            num_stages=1,
+            num_warps=2),
+        triton.Config(
+            {
+                'BLOCK_M': 32,
+                'BLOCK_N': 16,
+                'waves_per_eu': 4,
+                'PRE_LOAD_V': False
+            },
+            num_stages=1,
+            num_warps=2),
+        triton.Config(
+            {
+                'BLOCK_M': 32,
+                'BLOCK_N': 16,
+                'waves_per_eu': 2,
+                'PRE_LOAD_V': False
+            },
+            num_stages=1,
+            num_warps=2),
+        # Fails in AccelerateAMDMatmul (Triton) assert when using FP8:
+        # triton.Config(
+        #     {
+        #         'BLOCK_M': 16,
+        #         'BLOCK_N': 16,
+        #         'waves_per_eu': 4,
+        #         'PRE_LOAD_V': False
+        #     },
+        #     num_stages=1,
+        #     num_warps=2),
+        # triton.Config(
+        #     {
+        #         'BLOCK_M': 16,
+        #         'BLOCK_N': 16,
+        #         'waves_per_eu': 2,
+        #         'PRE_LOAD_V': False
+        #     },
+        #     num_stages=1,
+        #     num_warps=2),
+        # # Fall-back config.
+        # triton.Config(
+        #     {
+        #         'BLOCK_M': 16,
+        #         'BLOCK_N': 16,
+        #         'waves_per_eu': 1,
+        #         'PRE_LOAD_V': False
+        #     },
+        #     num_stages=1,
+        #     num_warps=2),
+    ], ['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL', 'USE_FP8']
+
+
+def get_autotune_configs():
+    if is_navi():
+        return get_rdna_autotune_configs()
+    else:
+        return get_cdna_autotune_configs()
+
+
+autotune_configs, autotune_keys = get_autotune_configs()
+
+
+@triton.autotune(
+    configs=autotune_configs,
+    key=autotune_keys,
+    use_cuda_graph=True,
 )
 @triton.jit
 def attn_fwd(
@@ -833,6 +912,10 @@ def check_and_convert(t, scale):
         p_descale = 1.0 / p_scale
         o_descale = 1.0 / o_scale
 
+        if is_navi():
+            max_seqlens_q = 0
+            max_seqlens_k = 0
+
         attn_fwd[grid](
             q,
             k,