diff --git a/ggml/src/ggml-cuda/gated_delta_net.cu b/ggml/src/ggml-cuda/gated_delta_net.cu
index a7eb148e4e..7c50b03960 100644
--- a/ggml/src/ggml-cuda/gated_delta_net.cu
+++ b/ggml/src/ggml-cuda/gated_delta_net.cu
@@ -43,10 +43,10 @@ __global__ void gated_delta_net_cuda(const float * q,
 
     constexpr int warp_size = ggml_cuda_get_physical_warp_size() < S_v ? ggml_cuda_get_physical_warp_size() : S_v;
     static_assert(S_v % warp_size == 0, "S_v must be a multiple of warp_size");
-    constexpr int ROWS_PER_LANE = (S_v + warp_size - 1) / warp_size;
-    float         s_shard[ROWS_PER_LANE];
+    constexpr int rows_per_lane = (S_v + warp_size - 1) / warp_size;
+    float         s_shard[rows_per_lane];
 #pragma unroll
-    for (int r = 0; r < ROWS_PER_LANE; r++) {
+    for (int r = 0; r < rows_per_lane; r++) {
         const int i = r * warp_size + lane;
         s_shard[r]  = curr_state[i * S_v + col];
     }
@@ -68,7 +68,7 @@ __global__ void gated_delta_net_cuda(const float * q,
             // kv[col] = (S^T @ k)[col] = sum_i S[i][col] * k[i]
             float kv_shard = 0.0f;
 #pragma unroll
-            for (int r = 0; r < ROWS_PER_LANE; r++) {
+            for (int r = 0; r < rows_per_lane; r++) {
                 const int i = r * warp_size + lane;
                 kv_shard += s_shard[r] * k_t[i];
             }
@@ -81,7 +81,7 @@ __global__ void gated_delta_net_cuda(const float * q,
             // attn[col] = (S^T @ q)[col] = sum_i S[i][col] * q[i]
             float attn_partial = 0.0f;
 #pragma unroll
-            for (int r = 0; r < ROWS_PER_LANE; r++) {
+            for (int r = 0; r < rows_per_lane; r++) {
                 const int i = r * warp_size + lane;
                 s_shard[r]  = g_val * s_shard[r] + k_t[i] * delta_col;
                 attn_partial += s_shard[r] * q_t[i];
@@ -96,7 +96,7 @@ __global__ void gated_delta_net_cuda(const float * q,
             // kv[col] = sum_i g[i] * S[i][col] * k[i]
             float kv_shard = 0.0f;
 #pragma unroll
-            for (int r = 0; r < ROWS_PER_LANE; r++) {
+            for (int r = 0; r < rows_per_lane; r++) {
                 const int i = r * warp_size + lane;
                 kv_shard += expf(g_t[i]) * s_shard[r] * k_t[i];
             }
@@ -110,7 +110,7 @@ __global__ void gated_delta_net_cuda(const float * q,
             // attn[col] = (S^T @ q)[col] = sum_i S[i][col] * q[i]
             float attn_partial = 0.0f;
 #pragma unroll
-            for (int r = 0; r < ROWS_PER_LANE; r++) {
+            for (int r = 0; r < rows_per_lane; r++) {
                 const int i = r * warp_size + lane;
                 s_shard[r]  = expf(g_t[i]) * s_shard[r] + k_t[i] * delta_col;
                 attn_partial += s_shard[r] * q_t[i];
@@ -128,7 +128,7 @@ __global__ void gated_delta_net_cuda(const float * q,
 
     // Write state back to global memory
 #pragma unroll
-    for (int r = 0; r < ROWS_PER_LANE; r++) {
+    for (int r = 0; r < rows_per_lane; r++) {
         const int i          = r * warp_size + lane;
         state[i * S_v + col] = s_shard[r];
     }