diff --git a/unsloth/kernels/rms_layernorm.py b/unsloth/kernels/rms_layernorm.py
index 4079921f91..3176d4e358 100644
--- a/unsloth/kernels/rms_layernorm.py
+++ b/unsloth/kernels/rms_layernorm.py
@@ -142,14 +142,14 @@ class Fast_RMS_Layernorm(torch.autograd.Function):
         n_rows : int
         n_cols : int
         n_rows, n_cols = X.shape
+        BLOCK_SIZE : int
+        num_warps  : int
+        BLOCK_SIZE, num_warps = calculate_settings(n_cols)
 
         Y = torch.empty((n_rows, n_cols), dtype = X.dtype, device = "cuda:0")
         r = torch.empty(n_rows, dtype = torch.float32, device = "cuda:0")
 
-        BLOCK_SIZE : int
-        num_warps  : int
         if not gemma:
-            BLOCK_SIZE, num_warps = calculate_settings(n_cols)
             _rms_layernorm_forward[(n_rows,)](
                 Y, Y.stride(0),
                 X, X.stride(0),
@@ -158,7 +158,7 @@ class Fast_RMS_Layernorm(torch.autograd.Function):
                 n_cols     = int(n_cols),
                 eps        = float(eps),
                 BLOCK_SIZE = BLOCK_SIZE,
-                num_warps  = num_warps,
+                num_warps  = 16,
             )
         else:
             _gemma_rms_layernorm_forward[(n_rows,)](
@@ -168,7 +168,7 @@ class Fast_RMS_Layernorm(torch.autograd.Function):
                 r, r.stride(0),
                 n_cols, eps,
                 BLOCK_SIZE = BLOCK_SIZE,
-                num_warps  = num_warps,
+                num_warps  = 16,
             )
         ctx.eps = eps
         ctx.BLOCK_SIZE = BLOCK_SIZE