diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
index 1f5af39e604e..f97ed3d6d511 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -231,8 +231,7 @@ static void generateFusedElementwiseOpRegion(
   // `consumerToProducerLoopsMap` to map the producer indices.
   if (producer.hasIndexSemantics()) {
     // Add an index operation for every fused loop dimension.
-    unsigned numFusedOpLoops =
-        std::max(producer.getNumLoops(), consumer.getNumLoops());
+    unsigned numFusedOpLoops = fusedOp.getNumLoops();
     SmallVector<Value> fusedIndices;
     fusedIndices.reserve(numFusedOpLoops);
     llvm::transform(llvm::seq<uint64_t>(0, numFusedOpLoops),
diff --git a/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir b/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir
index 28e1291bce1f..66fc55fadf8f 100644
--- a/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir
+++ b/mlir/test/Dialect/Linalg/fusion-elementwise-ops.mlir
@@ -860,6 +860,43 @@ func.func @fusion_different_axes(%arg0 : tensor<5000xi64>, %arg1 : tensor<5000xi
 
 // -----
 
+func.func @fusion_different_axes_indexed(%arg0: tensor<2x2xi32>) ->  tensor<2xi32> {
+  %0 = tensor.empty() : tensor<2x2xi32>
+  %1 = linalg.generic {
+        indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, affine_map<(d0, d1) -> (d0, d1)>],
+        iterator_types = ["parallel", "parallel"]}
+        ins(%arg0 : tensor<2x2xi32>) outs(%0 : tensor<2x2xi32>) {
+          ^bb0(%in: i32, %out: i32):
+            %2 = linalg.index 1 : index
+            %3 = arith.index_cast %2 : index to i32
+            linalg.yield %3 : i32
+        } -> tensor<2x2xi32>
+  %4 = tensor.empty() : tensor<2xi32>
+  %5 = linalg.generic {
+        indexing_maps = [affine_map<(d0) -> (d0, 1)>, affine_map<(d0) -> (d0)>],
+        iterator_types = ["parallel"]}
+        ins(%1 : tensor<2x2xi32>) outs(%4 : tensor<2xi32>) {
+          ^bb0(%in: i32, %out: i32):
+            linalg.yield %in : i32
+        } -> tensor<2xi32>
+  return %5 : tensor<2xi32>
+}
+
+//  CHECK-DAG: #[[MAP:.+]] = affine_map<(d0) -> (d0)>
+//      CHECK: func @fusion_different_axes_indexed(
+// CHECK-SAME:     %[[ARG0:.+]]: tensor<2x2xi32>
+//  CHECK-DAG:   %[[CST:.+]] = arith.constant 1 : i32
+//  CHECK-DAG:   %[[INIT:.+]] = tensor.empty() : tensor<2xi32>
+//      CHECK:   %[[RESULT:.+]] = linalg.generic
+// CHECK-SAME:       indexing_maps = [#[[MAP]]]
+// CHECK-SAME:       outs(%[[INIT]] :
+// CHECK-NEXT:   ^bb0(
+// CHECK-SAME:       %[[B0:.+]]: i32
+//      CHECK:     linalg.yield %[[CST]] : i32
+//      CHECK:   return %[[RESULT]]
+
+// -----
+
 // CHECK-LABEL: func @fold_fill_generic_basic
 //  CHECK-SAME: (%[[ARG0:.*]]: tensor<?xf32>) -> tensor<?xf32> {
 //   CHECK-NOT: linalg.fill