diff --git a/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags.py b/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags.py
index 53a79c3f5b92..08f7522d6267 100644
--- a/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags.py
+++ b/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags.py
@@ -3,7 +3,7 @@
 from dataclasses import dataclass
 
 import triton
-from triton_kernels.target_info import get_cdna_version
+from triton_kernels.target_info import get_cdna_version, get_rdna_version
 from triton_kernels.tensor import FP4
 import torch
 from .opt_flags_details import opt_flags_amd, opt_flags_nvidia
@@ -82,6 +82,8 @@ def make_default_opt_flags_amd(
         block_m = 256 if is_cdna4 else 128
     elif is_cdna4 and m >= 512:
         block_m = 128
+    elif get_rdna_version() in (3, 4) and m >= 512:
+        block_m = 64
     else:
         block_m = max(32, min(triton.next_power_of_2(tokens_per_expt), 64))
 
diff --git a/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags_details/opt_flags_amd.py b/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags_details/opt_flags_amd.py
index ffe06c333f60..598cbbac823b 100644
--- a/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags_details/opt_flags_amd.py
+++ b/python/triton_kernels/triton_kernels/matmul_ogs_details/opt_flags_details/opt_flags_amd.py
@@ -1,6 +1,6 @@
 import torch
 import triton
-from triton_kernels.target_info import get_cdna_version
+from triton_kernels.target_info import get_cdna_version, get_rdna_version
 from triton_kernels.tensor import bitwidth
 
 
@@ -23,11 +23,18 @@ def compute_block_nk(n, block_m, grid_m, num_xcds, lhs_dtype, rhs_dtype, precisi
     if get_cdna_version() == 4 and block_m == 128:
         block_n = 512
 
+    if get_rdna_version() in (3, 4) and block_m == 64:
+        block_n = 256
+
     # block_k needs to match the cacheline size (128B)
     block_k = int(128 // min(lhs_width, rhs_width))
 
     # TODO: block_k = 128 seems to work better for now.
     #       perhaps due to increased number of k loops to pipeline
-    if precision_config.weight_scale is not None and get_cdna_version() != 4:
-        block_k = 128
+    if precision_config.weight_scale is not None:
+        if get_cdna_version() != 4:
+            block_k = 128
+
+        if get_rdna_version() in (3, 4) and block_m == 64:
+            block_k = 64
     return block_n, block_k
diff --git a/python/triton_kernels/triton_kernels/target_info.py b/python/triton_kernels/triton_kernels/target_info.py
index 4350efa8b78a..b597e64f5aba 100644
--- a/python/triton_kernels/triton_kernels/target_info.py
+++ b/python/triton_kernels/triton_kernels/target_info.py
@@ -13,6 +13,7 @@
 __all__ = [
     "cuda_capability_geq",
     "get_cdna_version",
+    "get_rdna_version",
     "has_tma_gather",
     "has_native_mxfp",
     "is_cuda",
@@ -40,6 +41,23 @@ def get_cdna_version():
     return -1
 
 
+@triton.constexpr_function
+def get_rdna_version():
+    """
+    Gets the AMD architecture version, i.e. RDNA3 or RDNA4, by matching
+    gfx11* (RDNA3) or gfx12* (RDNA4). Returns -1 if it is not AMD
+    hardware or unsupported architecture.
+    """
+    target = tl.target_info.current_target()
+    if target.backend != 'hip':
+        return -1
+    if target.arch.startswith('gfx11'):
+        return 3
+    if target.arch.startswith('gfx12') and not target.arch.startswith('gfx125'):
+        return 4
+    return -1
+
+
 @triton.constexpr_function
 def has_tma_gather():
     return cuda_capability_geq(10, 0)