diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
index 0ac000e2bd978..85c7f05b83d95 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -1460,6 +1460,8 @@ def Tosa_ConcatOp : Tosa_Op<"concat", [
     Tosa_Tensor:$output
   );
 
+  let hasFolder = 1;
+
   let hasCanonicalizer = 1;
 
   let extraClassDeclaration = [{
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
index 97fb220b53290..8fdd6cf35500f 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
@@ -494,6 +494,30 @@ void SliceOp::getCanonicalizationPatterns(RewritePatternSet &results,
 // Operator Folders.
 //===----------------------------------------------------------------------===//
 
+static bool hasZeroSize(Type ty) {
+  auto ranked = dyn_cast<RankedTensorType>(ty);
+  if (!ranked)
+    return false;
+  return any_of(ranked.getShape(), [](auto d) { return d == 0; });
+}
+
+OpFoldResult ConcatOp::fold(FoldAdaptor adaptor) {
+  /// Remove operands that have zero elements.
+  bool changed = false;
+  for (size_t i = 0; i < getInput1().size(); ) {
+    auto input = getInput1()[i];
+    if (hasZeroSize(input.getType())) {
+      getInput1Mutable().erase(i);
+      changed = true;
+    } else {
+      ++i;
+    }
+  }
+  if (changed)
+    return getResult();
+  return {};
+}
+
 template <typename IntFolder, typename FloatFolder>
 DenseElementsAttr binaryFolder(DenseElementsAttr lhs, DenseElementsAttr rhs,
                                RankedTensorType returnTy) {
diff --git a/mlir/test/Dialect/Tosa/canonicalize.mlir b/mlir/test/Dialect/Tosa/canonicalize.mlir
index 4ad6ce65655ed..e049bc164150c 100644
--- a/mlir/test/Dialect/Tosa/canonicalize.mlir
+++ b/mlir/test/Dialect/Tosa/canonicalize.mlir
@@ -86,6 +86,13 @@ func.func @clamp_twice_is_single_clamp(%arg0: tensor<4xi8>) -> tensor<4xi8> {
   return %1 : tensor<4xi8>
 }
 
+// CHECK-LABEL: @concat_fold_zero
+func.func @concat_fold_zero(%arg0: tensor<?x0xf32>, %arg1: tensor<?x1xf32>, %arg2: tensor<?x2xf32>) -> tensor<?x3xf32> {
+  // CHECK: "tosa.concat"(%arg1, %arg2) <{axis = 1 : i64}>
+  %0 = "tosa.concat"(%arg0, %arg1, %arg2) {axis = 1 : i64}: (tensor<?x0xf32>, tensor<?x1xf32>, tensor<?x2xf32>) -> tensor<?x3xf32>
+  return %0 : tensor<?x3xf32>
+}
+
 // CHECK-LABEL: @concat_fold
 func.func @concat_fold(%arg0: tensor<?x1xf32>) -> tensor<?x1xf32> {
   // CHECK: return %arg0