diff --git a/lib/Dialect/TritonGPU/IR/Dialect.cpp b/lib/Dialect/TritonGPU/IR/Dialect.cpp
index 65d36c713e02..32a22226a4fe 100644
--- a/lib/Dialect/TritonGPU/IR/Dialect.cpp
+++ b/lib/Dialect/TritonGPU/IR/Dialect.cpp
@@ -147,6 +147,20 @@ SmallVector<unsigned> getShapePerCTATile(Attribute layout) {
 }
 
 bool isExpensiveView(Type srcType, Type dstType) {
+  auto tensorSrcType = cast<RankedTensorType>(srcType);
+  auto tensorDstType = cast<RankedTensorType>(dstType);
+  auto llSrc =
+      toLinearLayout(tensorSrcType.getShape(), tensorSrcType.getEncoding());
+  auto llDst =
+      toLinearLayout(tensorDstType.getShape(), tensorDstType.getEncoding());
+  // In case there are replicated value we need to make sure the new and old
+  // layout have matching masks.
+  for (auto [srcMask, dstMask] :
+       llvm::zip(llSrc.getFreeVariableMasks(), llDst.getFreeVariableMasks())) {
+    assert(srcMask.first == dstMask.first);
+    if (srcMask.second != dstMask.second)
+      return true;
+  }
   return getTotalElemsPerThread(srcType) != getTotalElemsPerThread(dstType);
 }
 
diff --git a/test/TritonGPU/canonicalize.mlir b/test/TritonGPU/canonicalize.mlir
index fd794c7bd5ce..b96244996417 100644
--- a/test/TritonGPU/canonicalize.mlir
+++ b/test/TritonGPU/canonicalize.mlir
@@ -40,6 +40,25 @@ tt.func @test_canonicalize_convert_expensive_view(%arg0: tensor<256x16xf32, #blo
 
 // -----
 
+// test that the convert doesn't get combined with view if the resulting operations
+// is an expensive view which would require moving data across threads.
+// CHECK-LABEL: @test_canonicalize_convert_expensive_view
+// CHECK-SAME: (%[[ARG:.+]]: tensor<2xf32
+//       CHECK:   %[[C:.+]] = ttg.convert_layout %[[ARG]]
+//       CHECK:   %[[V:.+]] = tt.reshape %[[C]] allow_reorder
+//       CHECK:   tt.return %[[V]]
+#blocked = #ttg.blocked<{sizePerThread = [1, 1], threadsPerWarp = [8, 4], warpsPerCTA = [4, 1], order = [1, 0]}>
+#blocked1 = #ttg.blocked<{sizePerThread = [1], threadsPerWarp = [32], warpsPerCTA = [4], order = [0]}>
+module attributes {"ttg.num-ctas" = 1 : i32, "ttg.num-warps" = 4 : i32, ttg.target = "cuda:80"} {
+  tt.func @test_canonicalize_convert_expensive_view2(%arg0: tensor<2xf32, #ttg.slice<{dim = 1, parent = #blocked}>>) -> tensor<2xf32, #blocked1> {
+    %c = ttg.convert_layout %arg0 : tensor<2xf32, #ttg.slice<{dim = 1, parent = #blocked}>> -> tensor<2xf32, #blocked1>
+    %r = tt.reshape %c allow_reorder : tensor<2xf32, #blocked1> -> tensor<2xf32, #blocked1>
+    tt.return %r : tensor<2xf32, #blocked1>
+  }
+}
+
+// -----
+
 // test that the convert does get combined with the view even if the resulting operation
 // is an efficient view.
 // CHECK-LABEL: @test_canonicalize_convert_view