diff --git a/include/ttmlir/Dialect/TTIR/IR/TTIROps.td b/include/ttmlir/Dialect/TTIR/IR/TTIROps.td
index f17bbd018..99cae3ed2 100644
--- a/include/ttmlir/Dialect/TTIR/IR/TTIROps.td
+++ b/include/ttmlir/Dialect/TTIR/IR/TTIROps.td
@@ -217,6 +217,13 @@ def TTIR_SumOp : TTIR_ReductionOp<"sum"> {
     }];
 }
 
+def TTIR_MeanOp : TTIR_ReductionOp<"mean"> {
+  let summary = "Mean reduction op.";
+  let description = [{
+    Mean reduction op.
+  }];
+}
+
 def TTIR_SoftmaxOp : TTIR_DPSOp<"softmax"> {
     let summary = "Softmax operation.";
     let description = [{
diff --git a/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td b/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
index 4f060c67d..3457dca6d 100644
--- a/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
+++ b/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
@@ -124,6 +124,13 @@ def TTNN_SumOp : TTNN_ReductionOp<"sum"> {
     }];
 }
 
+def TTNN_MeanOp : TTNN_ReductionOp<"mean"> {
+  let summary = "Mean reduction op.";
+  let description = [{
+    Mean reduction op.
+  }];
+}
+
 def TTNN_ReluOp : TTNN_ElementwiseOp<"relu"> {
     let summary = "Eltwise ReLU.";
     let description = [{
diff --git a/include/ttmlir/Target/TTNN/program.fbs b/include/ttmlir/Target/TTNN/program.fbs
index a2251c1cb..b9ab19242 100644
--- a/include/ttmlir/Target/TTNN/program.fbs
+++ b/include/ttmlir/Target/TTNN/program.fbs
@@ -40,6 +40,7 @@ table EltwiseOp {
 
 enum ReductionOpType: uint32 {
   Sum = 0,
+  Mean = 1,
 }
 
 table ReductionOp {
diff --git a/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp b/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
index 9501ca7f2..831c00c7c 100644
--- a/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
+++ b/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
@@ -144,6 +144,7 @@ void populateTTIRToTTNNPatterns(MLIRContext *ctx, RewritePatternSet &patterns,
            ElementwiseBinaryOpConversionPattern<ttir::GreaterEqualOp, ttnn::GreaterEqualOp>,
            ElementwiseBinaryOpConversionPattern<ttir::ReluOp, ttnn::ReluOp>,
            ReductionOpConversionPattern<ttir::SumOp, ttnn::SumOp>,
+           ReductionOpConversionPattern<ttir::MeanOp, ttnn::MeanOp>,
            SoftmaxOpConversionPattern,
            MatmulOpConversionPattern
            >(typeConverter, ctx);
diff --git a/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp b/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
index d0fe6c9d1..ddeb81633 100644
--- a/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
+++ b/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
@@ -119,6 +119,7 @@ void populateTTNNToEmitCPatterns(mlir::MLIRContext *ctx,
   // Reduction ops
   //
   patterns.add<DefaultOpConversionPattern<ttnn::SumOp>>(typeConverter, ctx);
+  patterns.add<DefaultOpConversionPattern<ttnn::MeanOp>>(typeConverter, ctx);
 }
 
 } // namespace mlir::tt
diff --git a/lib/Dialect/TTIR/Transforms/Passes.cpp b/lib/Dialect/TTIR/Transforms/Passes.cpp
index 836108ca4..b3e5d754e 100644
--- a/lib/Dialect/TTIR/Transforms/Passes.cpp
+++ b/lib/Dialect/TTIR/Transforms/Passes.cpp
@@ -535,6 +535,7 @@ class TTIRLayout : public impl::TTIRLayoutBase<TTIRLayout> {
           TTIRLayoutOperandsRewriter<SubtractOp>,
           TTIRLayoutOperandsRewriter<GreaterEqualOp>,
           TTIRLayoutOperandsRewriter<ReluOp>, TTIRLayoutOperandsRewriter<SumOp>,
+          TTIRLayoutOperandsRewriter<MeanOp>,
           TTIRLayoutOperandsRewriter<SoftmaxOp>,
           TTIRLayoutOperandsRewriter<MatmulOp>, TTIRLayoutFuncReturnRewriter>(
           &getContext());
diff --git a/lib/Target/TTNN/TTNNToFlatbuffer.cpp b/lib/Target/TTNN/TTNNToFlatbuffer.cpp
index 5660d8607..9d7376cb1 100644
--- a/lib/Target/TTNN/TTNNToFlatbuffer.cpp
+++ b/lib/Target/TTNN/TTNNToFlatbuffer.cpp
@@ -142,6 +142,8 @@ createReductionOp(FlatbufferObjectCache &cache, ReductionOp op) {
   ::tt::target::ttnn::ReductionOpType type;
   if constexpr (std::is_same_v<ReductionOp, SumOp>) {
     type = ::tt::target::ttnn::ReductionOpType::Sum;
+  } else if constexpr (std::is_same_v<ReductionOp, MeanOp>) {
+    type = ::tt::target::ttnn::ReductionOpType::Mean;
   } else {
     llvm_unreachable("unhandled ReductionOp");
   }
@@ -209,6 +211,10 @@ emitTTNNOperation(FlatbufferObjectCache &cache, Operation *op,
   if (auto sumOp = dyn_cast<SumOp>(op); sumOp) {
     return createOperation(cache, createReductionOp(cache, sumOp), debugString);
   }
+  if (auto meanOp = dyn_cast<MeanOp>(op); meanOp) {
+    return createOperation(cache, createReductionOp(cache, meanOp),
+                           debugString);
+  }
   if (auto softmaxOp = dyn_cast<SoftmaxOp>(op); softmaxOp) {
     return createOperation(cache, createSoftmaxOp(cache, softmaxOp),
                            debugString);
diff --git a/runtime/lib/ttnn/program.cpp b/runtime/lib/ttnn/program.cpp
index 0ee4cc88e..59ce43f54 100644
--- a/runtime/lib/ttnn/program.cpp
+++ b/runtime/lib/ttnn/program.cpp
@@ -247,6 +247,20 @@ run(::tt::target::ttnn::ReductionOp const *op, ::ttnn::Device &device,
     liveTensors.try_emplace(op->out()->global_id(), &tensorPool.back());
     break;
   }
+  case ::tt::target::ttnn::ReductionOpType::Mean: {
+    auto &in = *liveTensors.at(op->in()->global_id());
+
+    const auto *dim_arg_fb_ptr = op->dim_arg();
+    std::optional<vector<int>> dim_arg =
+        dim_arg_fb_ptr ? std::make_optional(std::vector<int>(
+                             dim_arg_fb_ptr->begin(), dim_arg_fb_ptr->end()))
+                       : std::nullopt;
+
+    tensorPool.push_back(::ttnn::mean(in, dim_arg, op->keep_dim()));
+
+    liveTensors.try_emplace(op->out()->global_id(), &tensorPool.back());
+    break;
+  }
   }
 }
 
diff --git a/test/ttmlir/Dialect/TTNN/simple_mean.mlir b/test/ttmlir/Dialect/TTNN/simple_mean.mlir
new file mode 100644
index 000000000..fe2f586af
--- /dev/null
+++ b/test/ttmlir/Dialect/TTNN/simple_mean.mlir
@@ -0,0 +1,15 @@
+// RUN: ttmlir-opt --ttir-layout --ttnn-open-device --convert-ttir-to-ttnn %s | FileCheck %s
+#any_device = #tt.operand_constraint<dram|l1|tile|any_device|any_device_tile>
+module attributes {tt.system_desc = #tt.system_desc<[{arch = <wormhole_b0>, grid = 8x8, l1_size = 1048576, num_dram_channels = 12, dram_channel_size = 1048576, noc_l1_address_align_bytes = 16, pcie_address_align_bytes = 32, noc_dram_address_align_bytes = 32}], [0], [<pcie|host_mmio>], [<0, 0, 0, 0>]>} {
+  func.func @forward(%arg0: tensor<512x1024xbf16>) -> tensor<512x32xbf16> {
+    // CHECK: %[[C:.*]] = "ttnn.open_device"[[C:.*]]
+    // CHECK: %[[C:.*]] = "ttnn.full"[[C:.*]]
+    %0 = tensor.empty() : tensor<512x32xbf16>
+    // CHECK: %[[C:.*]] = "ttnn.to_memory_config"[[C:.*]]
+    // CHECK: %[[C:.*]] = "ttnn.mean"[[C:.*]]
+    %1 = "ttir.mean"(%arg0, %0) <{dim_arg = [-1: i32], keep_dim = true, operand_constraints = [#any_device, #any_device]}> : (tensor<512x1024xbf16>, tensor<512x32xbf16>) -> tensor<512x32xbf16>
+    // CHECK: %[[C:.*]] = "ttnn.to_memory_config"[[C:.*]]
+    // CHECK: "ttnn.close_device"[[C:.*]]
+    return %1 : tensor<512x32xbf16>
+  }
+}