diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -1556,6 +1556,7 @@
     Tosa_Tensor1Dto6D:$output
   );
 
+  let hasCanonicalizer = 1;
   let hasFolder = 1;
 }
 
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
--- a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
@@ -519,6 +519,65 @@
   results.add<ClampClampOptimization>(context);
 }
 
+struct ConcatSliceOptimization : public OpRewritePattern<tosa::SliceOp> {
+  using OpRewritePattern<tosa::SliceOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(tosa::SliceOp sliceOp,
+                                PatternRewriter &rewriter) const override {
+    Value sliceInput = sliceOp.getInput();
+    auto concatOp = sliceInput.getDefiningOp<tosa::ConcatOp>();
+    if (!concatOp)
+      return rewriter.notifyMatchFailure(
+          sliceOp, "slice input must be concat operation");
+
+    OperandRange inputs = concatOp.getInput1();
+    auto concatType = dyn_cast<RankedTensorType>(concatOp.getType());
+    if (!concatType || !concatType.hasStaticShape())
+      return rewriter.notifyMatchFailure(
+          sliceOp, "slice input must be a static ranked tensor");
+    int32_t axis = concatOp.getAxis();
+
+    llvm::SmallVector<int64_t> sliceStart(sliceOp.getStart());
+    llvm::ArrayRef<int64_t> sliceSize = sliceOp.getSize();
+
+    // Validate slice on the concatenated axis. Slicing along this
+    // axis should span only one of the inputs to the concatenate
+    // operation.
+    std::optional<Value> replaceWithSlice;
+    for (auto input : inputs) {
+      auto inputType = dyn_cast<RankedTensorType>(input.getType());
+      if (!inputType || !inputType.hasStaticShape())
+        return rewriter.notifyMatchFailure(
+            sliceOp, "concat input must be a static ranked tensor");
+
+      if (sliceStart[axis] >= 0 &&
+          (sliceStart[axis] + sliceSize[axis]) <= inputType.getDimSize(axis)) {
+        replaceWithSlice =
+            rewriter
+                .create<tosa::SliceOp>(
+                    sliceOp.getLoc(), sliceOp.getType(), input,
+                    rewriter.getDenseI64ArrayAttr(sliceOp.getStart()),
+                    rewriter.getDenseI64ArrayAttr(sliceSize))
+                .getResult();
+        break;
+      }
+      sliceStart[axis] -= inputType.getDimSize(axis);
+    }
+
+    if (!replaceWithSlice)
+      return rewriter.notifyMatchFailure(
+          sliceOp, "corresponding concat input not found for slice");
+
+    rewriter.replaceOp(sliceOp, replaceWithSlice.value());
+    return success();
+  }
+};
+
+void SliceOp::getCanonicalizationPatterns(RewritePatternSet &results,
+                                          MLIRContext *context) {
+  results.add<ConcatSliceOptimization>(context);
+}
+
 //===----------------------------------------------------------------------===//
 // Operator Folders.
 //===----------------------------------------------------------------------===//
diff --git a/mlir/test/Dialect/Tosa/canonicalize.mlir b/mlir/test/Dialect/Tosa/canonicalize.mlir
--- a/mlir/test/Dialect/Tosa/canonicalize.mlir
+++ b/mlir/test/Dialect/Tosa/canonicalize.mlir
@@ -434,3 +434,56 @@
   %resize = "tosa.resize"(%arg0) {mode = "BILINEAR", scale = array<i64: 2, 2, 1, 1>, offset = array<i64: 0, 0>, border = array<i64: 0, 0>} : (tensor<1x15x13x1xi8>) -> tensor<1x15x13x1xi8>
   return %resize : tensor<1x15x13x1xi8>
 }
+
+// -----
+
+// CHECK-LABEL: @canonicalize_concat_slice_final_axis
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x12x12x1xf32>, %[[VAL_1:.*]]: tensor<1x12x12x1xf32>
+// CHECK: return %[[VAL_0]], %[[VAL_1]] : tensor<1x12x12x1xf32>, tensor<1x12x12x1xf32>
+func.func @canonicalize_concat_slice_final_axis(%arg0 : tensor<1x12x12x1xf32>, %arg1 : tensor<1x12x12x1xf32>) -> (tensor<1x12x12x1xf32>, tensor<1x12x12x1xf32>) {
+  %0 = "tosa.concat"(%arg0, %arg1) {axis = 3 : i64} : (tensor<1x12x12x1xf32>, tensor<1x12x12x1xf32>) -> tensor<1x12x12x2xf32>
+  %1 = "tosa.slice"(%0) {size = array<i64: 1, 12, 12, 1>, start = array<i64: 0, 0, 0, 0>} : (tensor<1x12x12x2xf32>) -> tensor<1x12x12x1xf32>
+  %2 = "tosa.slice"(%0) {size = array<i64: 1, 12, 12, 1>, start = array<i64: 0, 0, 0, 1>} : (tensor<1x12x12x2xf32>) -> tensor<1x12x12x1xf32>
+  return %1, %2 : tensor<1x12x12x1xf32>, tensor<1x12x12x1xf32>
+}
+
+// -----
+
+// CHECK-LABEL: @canonicalize_concat_slice_middle_axis
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x12x12xf32>, %[[VAL_1:.*]]: tensor<1x12x12xf32>
+// CHECK: return %[[VAL_0]], %[[VAL_1]] : tensor<1x12x12xf32>, tensor<1x12x12xf32>
+func.func @canonicalize_concat_slice_middle_axis(%arg0 : tensor<1x12x12xf32>, %arg1 : tensor<1x12x12xf32>) -> (tensor<1x12x12xf32>, tensor<1x12x12xf32>) {
+  %0 = "tosa.concat"(%arg0, %arg1) {axis = 1 : i64} : (tensor<1x12x12xf32>, tensor<1x12x12xf32>) -> tensor<1x24x12xf32>
+  %1 = "tosa.slice"(%0) {size = array<i64: 1, 12, 12>, start = array<i64: 0, 0, 0>} : (tensor<1x24x12xf32>) -> tensor<1x12x12xf32>
+  %2 = "tosa.slice"(%0) {size = array<i64: 1, 12, 12>, start = array<i64: 0, 12, 0>} : (tensor<1x24x12xf32>) -> tensor<1x12x12xf32>
+  return %1, %2 : tensor<1x12x12xf32>, tensor<1x12x12xf32>
+}
+
+// -----
+
+// CHECK-LABEL: @canonicalize_cross_concat_inputs
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x12x12xf32>, %[[VAL_1:.*]]: tensor<1x12x12xf32>
+// CHECK: %[[VAL_2:.*]] = "tosa.concat"(%[[VAL_0]], %[[VAL_1]]) {axis = 2 : i64} : (tensor<1x12x12xf32>, tensor<1x12x12xf32>) -> tensor<1x12x24xf32>
+// CHECK: %[[VAL_3:.*]] = "tosa.slice"(%[[VAL_2]]) {size = array<i64: 1, 12, 15>, start = array<i64: 0, 0, 0>} : (tensor<1x12x24xf32>) -> tensor<1x12x15xf32>
+// CHECK: %[[VAL_4:.*]] = "tosa.slice"(%[[VAL_2]]) {size = array<i64: 1, 12, 20>, start = array<i64: 0, 0, 4>} : (tensor<1x12x24xf32>) -> tensor<1x12x20xf32>
+// CHECK: return %[[VAL_3]], %[[VAL_4]] : tensor<1x12x15xf32>, tensor<1x12x20xf32>
+func.func @canonicalize_cross_concat_inputs(%arg0 : tensor<1x12x12xf32>, %arg1 : tensor<1x12x12xf32>) -> (tensor<1x12x15xf32>, tensor<1x12x20xf32>) {
+  %0 = "tosa.concat"(%arg0, %arg1) {axis = 2 : i64} : (tensor<1x12x12xf32>, tensor<1x12x12xf32>) -> tensor<1x12x24xf32>
+  %1 = "tosa.slice"(%0) {size = array<i64: 1, 12, 15>, start = array<i64: 0, 0, 0>} : (tensor<1x12x24xf32>) -> tensor<1x12x15xf32>
+  %2 = "tosa.slice"(%0) {size = array<i64: 1, 12, 20>, start = array<i64: 0, 0, 4>} : (tensor<1x12x24xf32>) -> tensor<1x12x20xf32>
+  return %1, %2 : tensor<1x12x15xf32>, tensor<1x12x20xf32>
+}
+
+// -----
+
+// CHECK-LABEL: @canonicalize_concat_slice_on_non_concat_axis
+// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x12x12xf32>, %[[VAL_1:.*]]: tensor<1x12x12xf32>
+// CHECK: %[[VAL_2:.*]] = "tosa.slice"(%[[VAL_0]]) {size = array<i64: 1, 6, 12>, start = array<i64: 0, 0, 0>} : (tensor<1x12x12xf32>) -> tensor<1x6x12xf32>
+// CHECK: %[[VAL_3:.*]] = "tosa.slice"(%[[VAL_1]]) {size = array<i64: 1, 3, 12>, start = array<i64: 1, 3, 12>} : (tensor<1x12x12xf32>) -> tensor<1x3x12xf32>
+// CHECK: return %[[VAL_2]], %[[VAL_3]] : tensor<1x6x12xf32>, tensor<1x3x12xf32>
+func.func @canonicalize_concat_slice_on_non_concat_axis(%arg0 : tensor<1x12x12xf32>, %arg1 : tensor<1x12x12xf32>) -> (tensor<1x6x12xf32>, tensor<1x3x12xf32>) {
+  %0 = "tosa.concat"(%arg0, %arg1) {axis = 2 : i64} : (tensor<1x12x12xf32>, tensor<1x12x12xf32>) -> tensor<1x12x24xf32>
+  %1 = "tosa.slice"(%0) {size = array<i64: 1, 6, 12>, start = array<i64: 0, 0, 0>} : (tensor<1x12x24xf32>) -> tensor<1x6x12xf32>
+  %2 = "tosa.slice"(%0) {size = array<i64: 1, 3, 12>, start = array<i64: 1, 3, 12>} : (tensor<1x12x24xf32>) -> tensor<1x3x12xf32>
+  return %1, %2 : tensor<1x6x12xf32>, tensor<1x3x12xf32>
+}