diff --git a/mlir/lib/IR/BuiltinAttributes.cpp b/mlir/lib/IR/BuiltinAttributes.cpp
--- a/mlir/lib/IR/BuiltinAttributes.cpp
+++ b/mlir/lib/IR/BuiltinAttributes.cpp
@@ -696,8 +696,8 @@
   size_t storageBitWidth = getDenseElementStorageWidth(bitWidth);
 
   // Compress the attribute values into a character buffer.
-  SmallVector<char, 8> data(llvm::divideCeil(storageBitWidth, CHAR_BIT) *
-                            values.size());
+  SmallVector<char, 8> data(
+      llvm::divideCeil(storageBitWidth * values.size(), CHAR_BIT));
   APInt intVal;
   for (unsigned i = 0, e = values.size(); i < e; ++i) {
     assert(eltType == values[i].getType() &&
@@ -1027,7 +1027,7 @@
 template <typename APRangeT>
 static void writeAPIntsToBuffer(size_t storageWidth, std::vector<char> &data,
                                 APRangeT &&values) {
-  data.resize(llvm::divideCeil(storageWidth, CHAR_BIT) * llvm::size(values));
+  data.resize(llvm::divideCeil(storageWidth * llvm::size(values), CHAR_BIT));
   size_t offset = 0;
   for (auto it = values.begin(), e = values.end(); it != e;
        ++it, offset += storageWidth) {
@@ -1184,7 +1184,7 @@
     assert(newArrayType && "Unhandled tensor type");
 
   size_t numRawElements = attr.isSplat() ? 1 : newArrayType.getNumElements();
-  data.resize(llvm::divideCeil(storageBitWidth, CHAR_BIT) * numRawElements);
+  data.resize(llvm::divideCeil(storageBitWidth * numRawElements, CHAR_BIT));
 
   // Functor used to process a single element value of the attribute.
   auto processElt = [&](decltype(*attr.begin()) value, size_t index) {
diff --git a/mlir/test/IR/attribute-roundtrip.mlir b/mlir/test/IR/attribute-roundtrip.mlir
new file mode 100644
--- /dev/null
+++ b/mlir/test/IR/attribute-roundtrip.mlir
@@ -0,0 +1,10 @@
+// RUN: mlir-opt -canonicalize %s | mlir-opt | FileCheck %s
+
+// CHECK-LABEL: @large_i1_tensor_roundtrip
+func @large_i1_tensor_roundtrip() -> tensor<160xi1> {
+  %cst_0 = arith.constant dense<"0xFFF00000FF000000FF000000FF000000FF000000"> : tensor<160xi1>
+  %cst_1 = arith.constant dense<"0xFF000000FF000000FF000000FF000000FF0000F0"> : tensor<160xi1>
+  // CHECK: dense<"0xFF000000FF000000FF000000FF000000FF000000">
+  %0 = arith.andi %cst_0, %cst_1 : tensor<160xi1>
+  return %0 : tensor<160xi1>
+}
diff --git a/mlir/test/Target/SPIRV/constant.mlir b/mlir/test/Target/SPIRV/constant.mlir
--- a/mlir/test/Target/SPIRV/constant.mlir
+++ b/mlir/test/Target/SPIRV/constant.mlir
@@ -159,7 +159,7 @@
   spv.func @bool_vector_const() -> () "None" {
     // CHECK: spv.Constant dense<false> : vector<2xi1>
     %0 = spv.Constant dense<false> : vector<2xi1>
-    // CHECK: spv.Constant dense<[true, true, true]> : vector<3xi1>
+    // CHECK: spv.Constant dense<true> : vector<3xi1>
     %1 = spv.Constant dense<true> : vector<3xi1>
     // CHECK: spv.Constant dense<[false, true]> : vector<2xi1>
     %2 = spv.Constant dense<[false, true]> : vector<2xi1>