diff --git a/src/plugins/intel_cpu/src/cpu_memory.cpp b/src/plugins/intel_cpu/src/cpu_memory.cpp
index 19efccff0f8..f6cc713d4e2 100644
--- a/src/plugins/intel_cpu/src/cpu_memory.cpp
+++ b/src/plugins/intel_cpu/src/cpu_memory.cpp
@@ -2,24 +2,8 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <oneapi/dnnl/dnnl.hpp>
-#include <vector>
-#include <numeric>
-#include <unordered_set>
-
-#include <dnnl_types.h>
-#include <common/memory_desc_wrapper.hpp>
 #include "cpu_memory.h"
-#include "nodes/common/cpu_memcpy.h"
-#include "nodes/common/cpu_convert.h"
-#include "onednn/dnnl.h"
-#include "cpu_shape.h"
-#include "memory_desc/dnnl_blocked_memory_desc.h"
 #include "nodes/reorder.h"
-#include "memory_desc/cpu_memory_desc.h"
-
-using namespace InferenceEngine;
-using namespace dnnl;
 
 namespace ov {
 namespace intel_cpu {
@@ -169,7 +153,7 @@ dnnl::memory Memory::DnnlMemPrimHandle::getPrim() const {
         // Equivalent of constructor memory(const primitive_desc &desc, void *hdl)
         // but with ability to skip pads zeroing.
         auto desc = MemoryDescUtils::convertToDnnlMemoryDesc(m_memObjPtr->getDescPtr());
-        m_prim = memory(desc->getDnnlDesc(), m_memObjPtr->getEngine(), DNNL_MEMORY_NONE);
+        m_prim = dnnl::memory(desc->getDnnlDesc(), m_memObjPtr->getEngine(), DNNL_MEMORY_NONE);
         //
         // ========================
         auto data = m_memObjPtr->getDataNoThrow();
@@ -288,6 +272,129 @@ void MemoryMngrRealloc::destroy(void *ptr) {
     dnnl::impl::free(ptr);
 }
 
+/////////////// StringMemory ///////////////
+
+StringMemory::StringMemory(const dnnl::engine& engine, const MemoryDescPtr& desc, const void* data) : m_engine(engine), m_mem_desc(desc) {
+    if (m_mem_desc->getPrecision() != element::string) {
+        OPENVINO_THROW("[CPU] StringMemory supports String type only.");
+    }
+
+    m_manager = std::make_shared<StringMemoryMngr>();
+
+    if (!m_mem_desc->isDefined()) {
+        return;
+    }
+
+    m_size = m_mem_desc->getCurrentMemSize();
+    const auto string_size = m_mem_desc->getShape().getElementsCount();
+
+    if (data != nullptr) {
+        auto not_const_data = const_cast<void *>(data);
+        m_manager->setExtBuff(reinterpret_cast<OvString *>(not_const_data), string_size);
+    } else {
+        m_manager->resize(string_size);
+    }
+}
+
+void StringMemory::load(const IMemory& src, bool ftz) const {
+    if (src.getDesc().getPrecision() != element::string) {
+        OPENVINO_THROW("[CPU] String memory cannot load a non-string object.");
+    }
+
+    transferData(src, *this, false);
+}
+
+void* StringMemory::getData() const  {
+    return m_manager->getRawPtr();
+}
+
+void StringMemory::redefineDesc(MemoryDescPtr desc) {
+    if (desc->getPrecision() != element::string) {
+        OPENVINO_THROW("[CPU] StringMemory supports String type only.");
+    }
+    if (!desc->hasDefinedMaxSize()) {
+        OPENVINO_THROW("[CPU] StringMemory cannot reset descriptor. Memory upper bound is unknown.");
+    }
+
+    m_mem_desc = desc;
+    const auto string_size = m_mem_desc->getShape().getElementsCount();
+    m_manager->resize(string_size);
+}
+
+void StringMemory::nullify() {
+    auto data_ptr = m_manager->getStringPtr();
+    if (data_ptr != nullptr) {
+        std::fill(data_ptr, data_ptr + m_manager->getStrLen(), OvString());
+    }
+}
+
+bool StringMemory::isAllocated() const noexcept {
+    if (getData()) {
+        return true;
+    }
+    if (!m_mem_desc) {
+        return false;
+    }
+    if (!(m_mem_desc->isDefined())) {
+        return true;
+    }
+    if (m_mem_desc->getCurrentMemSize() == 0) {
+        return true;
+    }
+    return false;
+}
+
+MemoryMngrPtr StringMemory::getMemoryMngr() const {
+    OPENVINO_THROW("Unexpected call of StringMemory::getMemoryMngr()");
+}
+
+dnnl::memory StringMemory::getPrimitive() const {
+    OPENVINO_THROW("Unexpected call of StringMemory::getPrimitive()");
+}
+
+void StringMemory::StringMemoryMngr::setExtBuff(OvString* ptr, size_t size) {
+    m_use_external_storage = true;
+    m_str_upper_bound = size;
+    m_data = decltype(m_data)(ptr, release);
+}
+
+StringMemory::OvString* StringMemory::StringMemoryMngr::getStringPtr() const noexcept {
+    return m_data.get();
+}
+
+bool StringMemory::StringMemoryMngr::resize(size_t size) {
+    bool sizeChanged = false;
+    if (size > m_str_upper_bound) {
+        auto ptr = new OvString[size];
+        if (!ptr) {
+            OPENVINO_THROW("Failed to allocate ", size, " bytes of memory");
+        }
+        m_str_upper_bound = size;
+        m_use_external_storage = false;
+        m_data = decltype(m_data)(ptr, destroy);
+        sizeChanged = true;
+    }
+    return sizeChanged;
+}
+
+bool StringMemory::StringMemoryMngr::hasExtBuffer() const noexcept {
+    return m_use_external_storage;
+}
+
+size_t StringMemory::StringMemoryMngr::getStrLen() const noexcept {
+    return m_str_upper_bound;
+}
+
+void StringMemory::StringMemoryMngr::destroy(OvString* ptr) {
+    delete[] ptr;
+}
+
+void* StringMemory::StringMemoryMngr::getRawPtr() const noexcept {
+    return reinterpret_cast<void *>(m_data.get());
+}
+
+/////////////// DnnlMemoryMngr ///////////////
+
 void* DnnlMemoryMngr::getRawPtr() const noexcept {
     return m_pMemMngr->getRawPtr();
 }
@@ -348,7 +455,7 @@ StaticMemory::StaticMemory(const dnnl::engine& eng, MemoryDescPtr desc, const vo
         // ========================
         // Equivalent of constructor memory(const primitive_desc &desc, void *hdl)
         // but with ability to skip pads zeroing.
-        m_prim = memory(dnnl_desc->getDnnlDesc(), m_eng, DNNL_MEMORY_NONE);
+        m_prim = dnnl::memory(dnnl_desc->getDnnlDesc(), m_eng, DNNL_MEMORY_NONE);
         //
         // ========================
         if (pads_zeroing)
diff --git a/src/plugins/intel_cpu/src/cpu_memory.h b/src/plugins/intel_cpu/src/cpu_memory.h
index 4b3b8c5ca30..b734e3b000c 100644
--- a/src/plugins/intel_cpu/src/cpu_memory.h
+++ b/src/plugins/intel_cpu/src/cpu_memory.h
@@ -4,19 +4,8 @@
 
 #pragma once
 
-#include "ie_layouts.h"
-#include "memory_desc/cpu_memory_desc.h"
-#include "dnnl_extension_utils.h"
-#include "memory_desc/cpu_memory_desc_utils.h"
-#include <onednn/dnnl.h>
-#include <cpu_shape.h>
-
 #include "memory_desc/dnnl_memory_desc.h"
 
-#include <string>
-#include <functional>
-#include <memory>
-#include <vector>
 
 /**
  * @file contains a concept classes to work with memory/tensor/blob abstractions on plugin level.
@@ -364,8 +353,90 @@ private:
     }
 };
 
+class StringMemory : public IMemory {
+public:
+    using OvString = ov::element_type_traits<ov::element::string>::value_type;
+
+    class StringMemoryMngr {
+    public:
+        StringMemoryMngr() : m_data(nullptr, release) {}
+        OvString* getStringPtr() const noexcept;
+        void setExtBuff(OvString* ptr, size_t size);
+        size_t getStrLen() const noexcept;
+        void* getRawPtr() const noexcept;
+        bool resize(size_t size /* string elements number */);
+        bool hasExtBuffer() const noexcept;
+
+    private:
+        bool m_use_external_storage = false;
+        size_t m_str_upper_bound = 0lu;
+        std::unique_ptr<OvString, void (*)(OvString *)> m_data;
+
+        static void release(OvString* ptr) {}
+        static void destroy(OvString* ptr);
+    };
+
+    using StringMemoryMngrPtr = std::shared_ptr<StringMemoryMngr>;
+
+    StringMemory(const dnnl::engine& engine, const MemoryDescPtr& desc, const void* data = nullptr);
+
+    StringMemory(const dnnl::engine& engine, const MemoryDesc& desc, const void* data = nullptr)
+        : StringMemory(engine, desc.clone(), data) {}
+
+    StringMemory(const dnnl::engine& engine, const MemoryDescPtr& desc, const StringMemoryMngrPtr& manager)
+        : m_engine(engine), m_mem_desc(desc), m_manager(manager) {}
+
+    StringMemory(const dnnl::engine& engine, const MemoryDesc& desc, const StringMemoryMngrPtr& manager)
+        : StringMemory(engine, desc.clone(), manager) {}
+
+    bool isAllocated() const noexcept override;
+
+    const MemoryDesc& getDesc() const override {
+        return *m_mem_desc;
+    }
+
+    MemoryDescPtr getDescPtr() const override {
+        return m_mem_desc;
+    }
+
+    void* getData() const override;
+
+    size_t getSize() const override { // In bytes
+        return m_size;
+    }
+
+    const Shape& getShape() const override {
+        return m_mem_desc->getShape();
+    }
+
+    const VectorDims& getStaticDims() const override {
+        return m_mem_desc->getShape().getStaticDims();
+    }
+
+    void redefineDesc(MemoryDescPtr desc) override;
+
+    void load(const IMemory& src, bool ftz = false) const override;
+
+    MemoryMngrPtr getMemoryMngr() const override;
+
+    StringMemoryMngrPtr getStringMemoryMngrPtr() const {
+        return m_manager;
+    }
+
+    dnnl::memory getPrimitive() const override;
+
+    void nullify() override;
+
+private:
+    dnnl::engine m_engine;
+    MemoryDescPtr m_mem_desc;
+    StringMemoryMngrPtr m_manager;
+    size_t m_size;
+};
+
 using MemoryPtr = std::shared_ptr<IMemory>;
 using MemoryCPtr = std::shared_ptr<const IMemory>;
+using StringMemoryPtr = std::shared_ptr<StringMemory>;
 
 }   // namespace intel_cpu
 }   // namespace ov
diff --git a/src/plugins/intel_cpu/src/graph.cpp b/src/plugins/intel_cpu/src/graph.cpp
index 8b3646a37d4..d8c0d9ffc55 100644
--- a/src/plugins/intel_cpu/src/graph.cpp
+++ b/src/plugins/intel_cpu/src/graph.cpp
@@ -56,7 +56,6 @@
 
 using namespace dnnl;
 using namespace InferenceEngine;
-using namespace InferenceEngine::details;
 
 namespace ov {
 namespace intel_cpu {
@@ -605,6 +604,43 @@ void Graph::AllocateWithReuse() {
                 erase = true;
                 break;
             }
+
+            // Special allocation for string tensors
+            if (edge->getDesc().getPrecision() == element::string && edge->getStatus() == Edge::Status::NeedAllocation) {
+                StringMemory::StringMemoryMngrPtr mngr;
+                if (edge->getParent()->isConstant()) {
+                    if (edge->getParent()->getType() == Type::Input) {
+                        auto constNode = static_cast<node::Input *>(edge->getParent().get());
+                        edge->reuse(std::const_pointer_cast<IMemory>(constNode->getMemoryPtr()));
+                    } else {
+                        edge->externalAllocate(context->getWeightsCache());
+                    }
+                    auto stringMemory = dynamic_cast<StringMemory *>(edge->getMemoryPtr().get());
+                    OPENVINO_ASSERT(stringMemory, "[CPU] Edge between nodes '",
+                            edge->getParent()->getName(), "' and '", edge->getChild()->getName(), "' must have StringMemory.");
+                    mngr = stringMemory->getStringMemoryMngrPtr();
+                } else {
+                    auto memory = std::make_shared<StringMemory>(getEngine(), edge->getDesc());
+                    edge->reuse(memory);
+                    mngr = memory->getStringMemoryMngrPtr();
+                }
+                for (auto& edge_c : cluster) {
+                    if (edge_c == edge) {
+                        continue;
+                    }
+                    OPENVINO_ASSERT(edge_c->getDesc().getPrecision() == element::string, "All edges in the cluster must be string.");
+                    if (edge_c->getStatus() == Edge::Status::NotAllocated) {
+                        auto memory = std::make_shared<StringMemory>(getEngine(), edge_c->getDesc(), mngr);
+                        edge_c->reuse(memory);
+                    } else {
+                        OPENVINO_THROW("[CPU] String tensors allocation in the cluster. Edge between nodes '", edge_c->getParent()->getName(), "' and '",
+                            edge_c->getChild()->getName(), "' has an unexpected status: ", static_cast<int>(edge_c->getStatus()));
+                    }
+                }
+                erase = true;
+                continue;
+            }
+
             // Special allocation for constants
             if (edge->getStatus() != Edge::Status::NeedAllocation || !edge->getParent()->isConstant()) {
                 continue;
@@ -904,7 +940,10 @@ void Graph::PushInputData(const std::string& name, const ov::SoPtr<ITensor>& inp
             auto ext_tensor_desc = MemoryDescUtils::generateCpuBlockedMemoryDesc(input);
             auto actualDesc = edgeMemory->getDescPtr();
 
-            if (!actualDesc->isCompatible(*ext_tensor_desc)) {
+            if (actualDesc->getPrecision() == element::string) {
+                StringMemory ext_mem(getEngine(), ext_tensor_desc, ext_data_ptr);
+                edgeMemory->load(ext_mem);
+            } else if (!actualDesc->isCompatible(*ext_tensor_desc)) {
                 Memory ext_mem(getEngine(), ext_tensor_desc, ext_data_ptr, false);
                 edgeMemory->load(ext_mem, false);
             } else {
@@ -983,7 +1022,10 @@ void Graph::PullOutputData(std::unordered_map<std::string, ov::SoPtr<ITensor>>&
         // That is the same memory. No need to copy
         if (ext_blob_ptr == intr_blob_ptr) continue;
 
-        if (!actualDesc->isCompatible(*expected_desc_ptr) && !isScalarOutput) {
+        if (actualDesc->getPrecision() == element::string) {
+            StringMemory outBloMem(getEngine(), expected_desc_ptr, ext_blob_ptr);
+            outBloMem.load(intr_blob);
+        } else if (!actualDesc->isCompatible(*expected_desc_ptr) && !isScalarOutput) {
             Memory outBloMem(getEngine(), expected_desc_ptr, ext_blob_ptr, false);
             outBloMem.load(intr_blob, false);
         } else {
diff --git a/src/plugins/intel_cpu/src/infer_request.cpp b/src/plugins/intel_cpu/src/infer_request.cpp
index b3620b37623..5797d2991c8 100644
--- a/src/plugins/intel_cpu/src/infer_request.cpp
+++ b/src/plugins/intel_cpu/src/infer_request.cpp
@@ -26,6 +26,8 @@
 #include "utils/cpu_utils.hpp"
 #include "utils/general_utils.h"
 
+using OvString = ov::element_type_traits<ov::element::string>::value_type;
+
 namespace ov {
 namespace intel_cpu {
 SyncInferRequest::SyncInferRequest(std::shared_ptr<const CompiledModel> compiled_model)
@@ -173,11 +175,17 @@ std::vector<ov::ProfilingInfo> SyncInferRequest::get_profiling_info() const {
 }
 
 static inline void change_edge_ptr(const EdgePtr& edge, ov::SoPtr<ov::ITensor>& tensor) {
-    auto size = tensor->get_byte_size();
     auto& mem = edge->getMemory();
-    auto memMngr = mem.getMemoryMngr();
-    OPENVINO_ASSERT(memMngr);
-    memMngr->setExtBuff(tensor->data(), size);
+
+    if (tensor->get_element_type() == element::string) {
+        auto memMngr = dynamic_cast<const StringMemory &>(mem).getStringMemoryMngrPtr();
+        OPENVINO_ASSERT(memMngr);
+        memMngr->setExtBuff(tensor->data<OvString>(), tensor->get_size());
+    } else {
+        auto memMngr = mem.getMemoryMngr();
+        OPENVINO_ASSERT(memMngr);
+        memMngr->setExtBuff(tensor->data(), tensor->get_byte_size());
+    }
 }
 
 void SyncInferRequest::change_default_ptr() {
diff --git a/src/plugins/intel_cpu/src/nodes/common/cpu_convert.cpp b/src/plugins/intel_cpu/src/nodes/common/cpu_convert.cpp
index 58fcf70d494..6d65b51b93e 100644
--- a/src/plugins/intel_cpu/src/nodes/common/cpu_convert.cpp
+++ b/src/plugins/intel_cpu/src/nodes/common/cpu_convert.cpp
@@ -3,25 +3,19 @@
 //
 
 #include "cpu_convert.h"
+
 #include "cpu_memcpy.h"
-#include "openvino/core/parallel.hpp"
-#include <utils/bfloat16.hpp>
-#include <utils/general_utils.h>
-#include <selective_build.h>
-#include <openvino/core/type/float16.hpp>
-#include <algorithm>
-#include <type_traits>
-#include <tuple>
-#include <cmath>
-#include <onednn/dnnl.h>
+#include "utils/bfloat16.hpp"
+
 #if defined(OPENVINO_ARCH_X86_64)
 #include "nodes/kernels/x64/jit_kernel.hpp"
-#include <cpu/x64/jit_generator.hpp>
+#else
+#include "cpu_memory.h"
+#include "openvino/core/type/element_type_traits.hpp"
+#include "selective_build.h"
+#include "utils/general_utils.h"
 #endif
 
-using namespace InferenceEngine;
-
-
 namespace ov {
 namespace intel_cpu {
 namespace {
@@ -583,7 +577,11 @@ void cpu_convert(const void *srcPtr,
     if (srcPrc == dstPrc && srcPrc == interimPrc) {
         const size_t L2_cache_size = dnnl::utils::get_cache_size(2, true);
         const size_t totalSize = size * dstPrc.size();
-        if (totalSize >= L2_cache_size) {
+        if (srcPrc == element::string) {
+            auto str_src = reinterpret_cast<const StringMemory::OvString *>(srcPtr);
+            auto str_dst = reinterpret_cast<StringMemory::OvString *>(dstPtr);
+            std::copy(str_src, str_src + size, str_dst);
+        } else if (totalSize >= L2_cache_size) {
             auto src = static_cast<const uint8_t *>(srcPtr);
             auto dst = static_cast<uint8_t *>(dstPtr);
             parallel_nt(0, [&](const size_t ithr, const size_t nthr) {
diff --git a/src/plugins/intel_cpu/src/nodes/input.cpp b/src/plugins/intel_cpu/src/nodes/input.cpp
index 86f4d47a97f..4fbf8ebb3a4 100644
--- a/src/plugins/intel_cpu/src/nodes/input.cpp
+++ b/src/plugins/intel_cpu/src/nodes/input.cpp
@@ -3,28 +3,12 @@
 //
 
 #include "input.h"
-#include "common/cpu_memcpy.h"
-#include <dnnl_extension_utils.h>
 
-#include <string>
-#include <tuple>
-#include <algorithm>
-#include <cmath>
-#include <utils/general_utils.h>
+#include "cpu/x64/jit_generator.hpp"
 #include "openvino/core/parallel.hpp"
-#include <ie_ngraph_utils.hpp>
-#include "caseless.hpp"
-#include "common/cpu_memcpy.h"
-#include "common/cpu_convert.h"
-#include "utils/cpu_utils.hpp"
-#include <cpu/x64/jit_generator.hpp>
-#include "memory_desc/dnnl_blocked_memory_desc.h"
 #include "shape_inference/shape_inference_pass_through.hpp"
 
 using namespace dnnl;
-using namespace InferenceEngine;
-using namespace details;
-using namespace ov::op;
 using namespace dnnl::impl::cpu::x64;
 using namespace Xbyak;
 
@@ -234,11 +218,11 @@ jit_has_subnormals_base::fn_t jit_has_subnormals_function() {
 Input::Input(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr context)
         : Node(op, context, PassThroughShapeInferFactory()) {
     if (!one_of(op->get_type_info(),
-            v0::Parameter::get_type_info_static(),
-            v0::Constant::get_type_info_static(),
-            v0::Result::get_type_info_static(),
-            v3::ReadValue::get_type_info_static(),
-            v6::ReadValue::get_type_info_static()))
+            op::v0::Parameter::get_type_info_static(),
+            op::v0::Constant::get_type_info_static(),
+            op::v0::Result::get_type_info_static(),
+            op::v3::ReadValue::get_type_info_static(),
+            op::v6::ReadValue::get_type_info_static()))
         OPENVINO_THROW_NOT_IMPLEMENTED("CPU Input node doesn't support ngraph operation ",
                                        op->get_type_name(),
                                        " with name ",
@@ -246,7 +230,7 @@ Input::Input(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr conte
 
     constant = ConstantType::NoConst;
 
-    constOp = ov::as_type_ptr<ov::op::v0::Constant>(op);
+    constOp = ov::as_type_ptr<op::v0::Constant>(op);
     if (constOp) {
         constant = ConstantType::Const;
         cloneBlobIfRequired();
@@ -275,13 +259,29 @@ void Input::cloneBlobIfRequired() {
         // but ngraph Constant uses actual bitWidth for data storage allocation
         // in that case we make a copy to avoid overflow
         if (constOp->get_byte_size() >= memDesc.getCurrentMemSize()) {
-            memory = std::make_shared<Memory>(getEngine(), memDesc, constOp->get_data_ptr());
+            if (constOp->get_element_type() == element::string) {
+                memory = std::make_shared<StringMemory>(getEngine(), memDesc, constOp->get_data_ptr<element::string>());
+            } else {
+                memory = std::make_shared<Memory>(getEngine(), memDesc, constOp->get_data_ptr());
+            }
         } else {
-            memory = std::make_shared<Memory>(getEngine(), memDesc);
-            memcpy(memory->getData(), constOp->get_data_ptr(), constOp->get_byte_size());
+            if (constOp->get_element_type() == element::string) {
+                memory = std::make_shared<StringMemory>(getEngine(), memDesc);
+                auto src = constOp->get_data_ptr<StringMemory::OvString>();
+                auto dst = reinterpret_cast<StringMemory::OvString *>(memory->getData());
+                std::copy(src, src + size, dst);
+            } else {
+                memory = std::make_shared<Memory>(getEngine(), memDesc);
+                memcpy(memory->getData(), constOp->get_data_ptr(), constOp->get_byte_size());
+            }
         }
 
-        MemoryPtr ptr = std::make_shared<StaticMemory>(getEngine(), memDesc);
+        MemoryPtr ptr;
+        if (memDesc.getPrecision() == element::string) {
+            ptr = std::make_shared<StringMemory>(getEngine(), memDesc);
+        } else {
+            ptr = std::make_shared<StaticMemory>(getEngine(), memDesc);
+        }
         ptr->load(*memory.get(), needFlushDenormalsToZero);
 
         return ptr;
@@ -381,7 +381,7 @@ void Input::cloneBlobIfRequired() {
         memoryPtr = std::const_pointer_cast<const IMemory>(ptr);
     // IRs already have all subnormals flushed to zero, but in
     // read_model scenario with directly loaded original model still can have subnormals
-    } else if (isBlobAligned() && (!needFlushDenormalsToZero || !hasSubnormals()) && !isWA()) {
+    } else if (prec != element::string && isBlobAligned() && (!needFlushDenormalsToZero || !hasSubnormals()) && !isWA()) {
         memoryPtr = std::make_shared<Memory>(getEngine(), memDesc, constOp->get_data_ptr());
     } else {
         memoryPtr = std::const_pointer_cast<const IMemory>(cloneBlob());
@@ -420,14 +420,14 @@ MemoryCPtr Input::getMemoryPtr() const {
 void Input::getSupportedDescriptors() {
     if (getType() == Type::Input) {
         if (!getParentEdges().empty())
-            OPENVINO_THROW("Incorrect number of input edges for layer ", getName());
+            THROW_CPU_NODE_ERR("has incorrect number of input edges.");
         if (getChildEdges().empty())
-            OPENVINO_THROW("Incorrect number of output edges for layer ", getName());
+            THROW_CPU_NODE_ERR("has incorrect number of output edges.");
     } else if (getType() == Type::Output) {
         if (getParentEdges().size() != 1)
-            OPENVINO_THROW("Incorrect number of input edges for layer ", getName());
+            THROW_CPU_NODE_ERR("has incorrect number of input edges.");
         if (!getChildEdges().empty())
-            OPENVINO_THROW("Incorrect number of output edges for layer ", getName());
+            THROW_CPU_NODE_ERR("has incorrect number of output edges.");
     }
 }
 
@@ -446,19 +446,19 @@ void Input::createPrimitive() {
     for (size_t i = 0; i < getChildEdges().size(); i++) {
         auto dstMemPtr = getChildEdgeAt(i)->getMemoryPtr();
         if (!dstMemPtr || !dstMemPtr->isAllocated())
-            OPENVINO_THROW("Destination memory didn't allocate for node ", getName()
-                              , " to node ", getChildEdgeAt(i)->getChild()->getName(), ".");
+            THROW_CPU_NODE_ERR("has unallocated memory object at port ", i,
+                              " to node ", getChildEdgeAt(i)->getChild()->getName(), ".");
     }
     for (size_t i = 0; i < getParentEdges().size(); i++) {
         auto srcMemPtr = getParentEdgeAt(i)->getMemoryPtr();
         if (!srcMemPtr || !srcMemPtr->isAllocated())
-            OPENVINO_THROW("Destination memory didn't allocate for node ", getName()
-                              , " from node ", getParentEdgeAt(i)->getParent()->getName(), ".");
+            THROW_CPU_NODE_ERR("has unallocated memory object at port ", i,
+                              " from node ", getParentEdgeAt(i)->getParent()->getName(), ".");
     }
 
     const NodeDesc *selected_pd = getSelectedPrimitiveDescriptor();
     if (selected_pd == nullptr)
-        OPENVINO_THROW("Preferable primitive descriptor is not set for node ", getName(), ".");
+        THROW_CPU_NODE_ERR("doesn't have selected primitive descriptor.");
 }
 
 bool Input::created() const {
diff --git a/src/plugins/intel_cpu/src/nodes/input.h b/src/plugins/intel_cpu/src/nodes/input.h
index f8e5a4f1947..58daadccaff 100644
--- a/src/plugins/intel_cpu/src/nodes/input.h
+++ b/src/plugins/intel_cpu/src/nodes/input.h
@@ -4,10 +4,8 @@
 
 #pragma once
 
-#include <ie_common.h>
 #include <node.h>
 #include <openvino/op/constant.hpp>
-#include <string>
 
 namespace ov {
 namespace intel_cpu {
diff --git a/src/plugins/intel_cpu/src/nodes/reference.cpp b/src/plugins/intel_cpu/src/nodes/reference.cpp
index b7774985dac..327c54f9d55 100644
--- a/src/plugins/intel_cpu/src/nodes/reference.cpp
+++ b/src/plugins/intel_cpu/src/nodes/reference.cpp
@@ -3,13 +3,7 @@
 //
 
 #include "reference.h"
-
 #include "common/cpu_memcpy.h"
-#include <ie_ngraph_utils.hpp>
-#include "openvino/core/shape_util.hpp"
-
-using namespace InferenceEngine;
-using namespace InferenceEngine::details;
 
 namespace ov {
 namespace intel_cpu {
@@ -94,7 +88,13 @@ void Reference::executeDynamicImpl(dnnl::stream strm) {
             if (memory->getSize() != tensor.get_byte_size()) {
                 THROW_CPU_NODE_ERR("output tensor data size mismatch occurred during the inference on output port number ", i);
             }
-            cpu_memcpy(memory->getData(), tensor.data(), tensor.get_byte_size());
+            if (tensor.get_element_type() == element::string) {
+                auto srcPtr = tensor.data<StringMemory::OvString>();
+                auto dstPtr = reinterpret_cast<StringMemory::OvString *>(memory->getData());
+                std::copy(srcPtr, srcPtr + tensor.get_size(), dstPtr);
+            } else {
+                cpu_memcpy(memory->getData(), tensor.data(), tensor.get_byte_size());
+            }
         }
     }
 }
diff --git a/src/plugins/intel_cpu/src/nodes/reorder.cpp b/src/plugins/intel_cpu/src/nodes/reorder.cpp
index 8cf3ecee2fa..41b6509f70c 100644
--- a/src/plugins/intel_cpu/src/nodes/reorder.cpp
+++ b/src/plugins/intel_cpu/src/nodes/reorder.cpp
@@ -3,24 +3,14 @@
 //
 
 #include "reorder.h"
-#include <memory>
-#include <string>
-#include <algorithm>
-#include <dnnl_types.h>
-#include <dnnl_extension_utils.h>
-#include "openvino/core/parallel.hpp"
-#include "utils/general_utils.h"
-#include <cpu/x64/cpu_isa_traits.hpp>
-#include "nodes/common/cpu_memcpy.h"
-#include "nodes/common/cpu_convert.h"
-#include "nodes/common/reorder_prim.h"
-#include "convert.h"
-#include <common/primitive_hashing_utils.hpp>
-#include <shape_inference/shape_inference_pass_through.hpp>
-#include "executors/transpose_list.hpp"
 
-using namespace dnnl;
-using namespace InferenceEngine;
+#include "convert.h"
+#include "cpu/x64/cpu_isa_traits.hpp"
+#include "nodes/common/cpu_convert.h"
+#include "nodes/common/cpu_memcpy.h"
+#include "nodes/common/reorder_prim.h"
+#include "openvino/core/parallel.hpp"
+#include "shape_inference/shape_inference_pass_through.hpp"
 
 namespace ov {
 namespace intel_cpu {
@@ -32,7 +22,7 @@ bool Reorder::isExecutable() const {
 
 Reorder::Reorder(const std::shared_ptr<ov::Node>& op, const GraphContext::CPtr context) :
         Node(op, context, PassThroughShapeInferFactory()) {
-    OPENVINO_THROW("Can't create reorder node from ngraph node");
+    THROW_CPU_NODE_ERR("could not create CPU node from Core node.");
 }
 
 Reorder::Reorder(const std::string& name, const GraphContext::CPtr context) :
@@ -40,9 +30,9 @@ Reorder::Reorder(const std::string& name, const GraphContext::CPtr context) :
 
 void Reorder::getSupportedDescriptors() {
     if (getParentEdges().size() != 1)
-        OPENVINO_THROW("Incorrect number of input edges for layer ", getName());
+        THROW_CPU_NODE_ERR("has incorrect number of input edges.");
     if (getChildEdges().empty())
-        OPENVINO_THROW("Incorrect number of output edges for layer ", getName());
+        THROW_CPU_NODE_ERR("has incorrect number of output edges.");
 }
 
 void Reorder::initSupportedPrimitiveDescriptors() {
@@ -71,7 +61,7 @@ void Reorder::initSupportedPrimitiveDescriptors() {
         config.inConfs[0].setMemDesc(parent->getSelectedPrimitiveDescriptor()->getConfig().outConfs[0].getMemDesc());
         config.outConfs[0].setMemDesc(child->getSelectedPrimitiveDescriptor()->getConfig().inConfs[0].getMemDesc());
     } else {
-        OPENVINO_THROW("Cannot initialize supported PDs for Reorder node with name `", getName(), "`");
+        THROW_CPU_NODE_ERR("could not initialize supported PDs.");
     }
 
     supportedPrimitiveDescriptors.emplace_back(config, impl_desc_type::reorder);
@@ -83,9 +73,7 @@ void Reorder::initSupportedPrimitiveDescriptors() {
     }
 
     if (isDynamic && (config.inConfs[0].getMemDesc()->getShape().getRank() != config.outConfs[0].getMemDesc()->getShape().getRank()))
-        OPENVINO_THROW("Reorder node with name: ",
-                       getName(),
-                       " doesn't support case when input and output shapes have different rank and dynamic");
+        THROW_CPU_NODE_ERR("doesn't support case when input and output shapes have different rank and dynamic.");
     if (!isOptimized) {
         const auto &inShape = getInputShapeAtPort(0);
         if (one_of(inShape.getRank(), 4u, 5u) &&
@@ -95,7 +83,7 @@ void Reorder::initSupportedPrimitiveDescriptors() {
                 config.outConfs[0].getMemDesc()->getPrecision() == ov::element::f32) {
             // oneDNN JIT reorder shows bad perf for nspc to ncsp reorder case so we fallback on simple c++ implementation
             isNspc2NcspCase = true;
-        } else if (!impl::cpu::x64::mayiuse(impl::cpu::x64::avx2) &&
+        } else if (!dnnl::impl::cpu::x64::mayiuse(dnnl::impl::cpu::x64::avx2) &&
                    one_of(inShape.getRank(), 4u, 5u) &&
                    config.inConfs[0].getMemDesc()->hasLayoutType(LayoutType::ncsp) &&
                    config.outConfs[0].getMemDesc()->hasLayoutType(LayoutType::nspc) &&
@@ -180,11 +168,11 @@ void Reorder::prepareParams() {
     auto srcMemPtr = getParentEdgeAt(0)->getMemoryPtr();
     auto dstMemPtr = getChildEdgeAt(0)->getMemoryPtr();
     if (!dstMemPtr || !dstMemPtr->isAllocated())
-        OPENVINO_THROW("Destination memory didn't allocate.");
+        THROW_CPU_NODE_ERR("has unallocated destination memory object.");
     if (!srcMemPtr || !srcMemPtr->isAllocated())
-        OPENVINO_THROW("Input memory didn't allocate.");
+        THROW_CPU_NODE_ERR("has unallocated input memory object.");
     if (getSelectedPrimitiveDescriptor() == nullptr)
-        OPENVINO_THROW("Preferable primitive descriptor is not set.");
+        THROW_CPU_NODE_ERR("does not have preferable primitive descriptor.");
 
     auto isSupportedDesc = [](const MemoryDesc& desc) {
         if (!desc.isDefined()) {
@@ -239,11 +227,11 @@ void Reorder::prepareParams() {
     }
     if (!canUseNcsp2Nspc && !canUseNspc2Ncsp) {
         if (!dstMemPtr || !dstMemPtr->isAllocated())
-            OPENVINO_THROW("Destination memory didn't allocate.");
+            THROW_CPU_NODE_ERR("has unallocated destination memory object.");
         if (!srcMemPtr || !srcMemPtr->isAllocated())
-            OPENVINO_THROW("Input memory didn't allocate.");
+            THROW_CPU_NODE_ERR("has unallocated input memory object.");
         if (getSelectedPrimitiveDescriptor() == nullptr)
-            OPENVINO_THROW("Preferable primitive descriptor is not set.");
+            THROW_CPU_NODE_ERR("does not have preferable primitive descriptor.");
 
         createReorderPrimitive(srcMemPtr->getDescWithType<DnnlMemoryDesc>()->getDnnlDesc(), srcMemPtr->getData(),
                                dstMemPtr->getDescWithType<DnnlMemoryDesc>()->getDnnlDesc(), dstMemPtr->getData());
@@ -256,7 +244,7 @@ void Reorder::createReorderPrimitive(const dnnl::memory::desc& srcDesc,
                                      void* dstPtr) {
     auto selectedPD = getSelectedPrimitiveDescriptor();
     if (!selectedPD)
-        OPENVINO_THROW("Preferable primitive descriptor is not set.");
+        THROW_CPU_NODE_ERR("does not have preferable primitive descriptor.");
 
     const auto engine = getEngine();
     src_blocked = std::make_shared<Memory>(engine, DnnlExtensionUtils::makeDescriptor(srcDesc), srcPtr, false);
@@ -301,7 +289,7 @@ void Reorder::createReorderPrimitive(const dnnl::memory::desc& srcDesc,
 
     auto result = getReorderPrim(context->getParamsCache(), getEngine(), src_desc, dst_desc);
     if (!result) {
-        OPENVINO_THROW("Cannot create reorder primitive: unsupported reorder case");
+        THROW_CPU_NODE_ERR("could not create reorder primitive: unsupported reorder case.");
     }
     prim = result;
 
@@ -419,7 +407,7 @@ void Reorder::execute(dnnl::stream strm) {
         if (prim) {
             prim.execute(strm, primArgs);
         } else {
-            OPENVINO_THROW("Reorder node with name ", getName(), " doesn't have an initialized primitive");
+            THROW_CPU_NODE_ERR("doesn't have an initialized primitive.");
         }
     }
 }
@@ -448,11 +436,17 @@ void Reorder::reorderData(const IMemory &input, const IMemory &output, MultiCach
     }
 
     if (input.getDesc().isCompatible(output.getDesc())) {
-        auto srcPtr = static_cast<uint8_t*>(input.getData());
-        auto dstPtr = static_cast<uint8_t*>(output.getData());
+        if (input.getDesc().getPrecision() == element::string) {
+            auto srcPtr = reinterpret_cast<StringMemory::OvString *>(input.getData());
+            auto dstPtr = reinterpret_cast<StringMemory::OvString *>(output.getData());
+            std::copy(srcPtr, srcPtr + output.getShape().getElementsCount(), dstPtr);
+        } else {
+            auto srcPtr = static_cast<uint8_t*>(input.getData());
+            auto dstPtr = static_cast<uint8_t*>(output.getData());
 
-        auto copySize = output.getSize();
-        cpu_memcpy(dstPtr, srcPtr, copySize);
+            auto copySize = output.getSize();
+            cpu_memcpy(dstPtr, srcPtr, copySize);
+        }
     } else {
         dnnl::reorder reorder;
         std::vector<uint8_t> tmpBuff;
diff --git a/src/plugins/intel_cpu/src/nodes/reorder.h b/src/plugins/intel_cpu/src/nodes/reorder.h
index 1222549ac31..ffe43f0b56c 100644
--- a/src/plugins/intel_cpu/src/nodes/reorder.h
+++ b/src/plugins/intel_cpu/src/nodes/reorder.h
@@ -4,13 +4,11 @@
 
 #pragma once
 
-#include <ie_common.h>
 #include <node.h>
-#include <string>
-#include <memory>
-#include <vector>
+
+#if defined(OV_CPU_ARM_ENABLE_FP16)
 #include "nodes/executors/transpose.hpp"
-#include <utils/general_utils.h>
+#endif
 
 namespace ov {
 namespace intel_cpu {
diff --git a/src/plugins/intel_cpu/src/plugin.cpp b/src/plugins/intel_cpu/src/plugin.cpp
index 394db23ef58..779b6ef9fa2 100644
--- a/src/plugins/intel_cpu/src/plugin.cpp
+++ b/src/plugins/intel_cpu/src/plugin.cpp
@@ -533,7 +533,8 @@ Engine::compile_model(const std::shared_ptr<const ov::Model>& model, const ov::A
                                                                            ov::element::Type_t::f16,
                                                                            ov::element::Type_t::f32,
                                                                            ov::element::Type_t::f64,
-                                                                           ov::element::Type_t::boolean};
+                                                                           ov::element::Type_t::boolean,
+                                                                           ov::element::Type_t::string};
 
         if (!supported_precisions.count(input_precision)) {
             OPENVINO_THROW_NOT_IMPLEMENTED("CPU plugin: Input image format ",
diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/custom_op_string.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/custom_op_string.cpp
new file mode 100644
index 00000000000..34e92e3e59b
--- /dev/null
+++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/custom_op_string.cpp
@@ -0,0 +1,248 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+//      -----------------            ----------------
+//     |    Parameter    |          |    Constant    |
+//      -----------------            ----------------
+//         |  string  |                 | string |
+//   -----------    -----------------------    -----------
+//  | Extension |  |        Extension      |  | Extension |
+//   -----------    -----------------------    -----------
+//      | u8            | string       | string     | u8
+//   --------      -----------      --------      --------
+//  | Result |    | Extension |    | Result |    | Result |
+//   --------      -----------      --------      --------
+//                      | u8
+//               ---------------
+//              | Bitwise (CPU) |
+//               ---------------
+//                      | u8
+//                  --------
+//                 | Result |
+//                  --------
+
+#include "common_test_utils/ov_tensor_utils.hpp"
+#include "shared_test_classes/base/ov_subgraph.hpp"
+#include "test_utils/cpu_test_utils.hpp"
+
+using namespace CPUTestUtils;
+using namespace ov::test;
+
+namespace SubgraphTestsDefinitions {
+
+using CustomOpStringCPUTestParams = std::tuple<ElementType, InputShape>;
+
+class CustomOpStringString : public ov::op::Op {
+public:
+    OPENVINO_OP("CustomOpStringString");
+
+    CustomOpStringString() = default;
+    CustomOpStringString(const ov::OutputVector& args) : Op(args) {
+        constructor_validate_and_infer_types();
+    }
+
+    void validate_and_infer_types() override {
+        const auto& inputs_count = input_values().size();
+        OPENVINO_ASSERT(inputs_count == 2, "Input count must be 2, Got: ", inputs_count);
+        OPENVINO_ASSERT(get_input_element_type(0) == ov::element::Type_t::string, "The input must be string.");
+        OPENVINO_ASSERT(get_input_element_type(1) == ov::element::Type_t::string, "The input must be string.");
+
+        set_output_size(2);
+        set_output_type(0, ov::element::Type_t::string, get_input_partial_shape(0));
+        set_output_type(1, ov::element::Type_t::string, get_input_partial_shape(1));
+    }
+
+    std::shared_ptr<ov::Node> clone_with_new_inputs(const ov::OutputVector& new_args) const override {
+        OPENVINO_ASSERT(new_args.size() == 2, "Incorrect number of new arguments: ", new_args.size(), ". 2 is expected.");
+        return std::make_shared<CustomOpStringString>(new_args);
+    }
+
+    bool visit_attributes(ov::AttributeVisitor& visitor) override { return true; }
+
+    bool evaluate(ov::TensorVector& outputs, const ov::TensorVector& inputs) const override {
+        for (size_t i = 0lu; i < inputs.size(); i++) {
+            OPENVINO_ASSERT(inputs[i].get_shape().size() == static_cast<size_t>(get_input_partial_shape(i).rank().get_length()),
+                "Invalid input shape rank: ", inputs[i].get_shape().size());
+        }
+        for (size_t i = 0lu; i < outputs.size(); i++) {
+            OPENVINO_ASSERT(outputs[i].get_shape().size() == static_cast<size_t>(get_output_partial_shape(i).rank().get_length()),
+                "Invalid outputs shape rank: ", outputs[i].get_shape().size());
+        }
+
+        auto in_data_0 = inputs[0].data<ov::element_type_traits<ov::element::string>::value_type>();
+        auto in_data_1 = inputs[1].data<ov::element_type_traits<ov::element::string>::value_type>();
+        auto out_data_0 = outputs[0].data<ov::element_type_traits<ov::element::string>::value_type>();
+        auto out_data_1 = outputs[1].data<ov::element_type_traits<ov::element::string>::value_type>();
+
+        const auto el_num_0 = outputs[0].get_size();
+        for (size_t i = 0lu; i < el_num_0; i++) {
+            out_data_0[i] = in_data_0[i];
+        }
+
+        const auto el_num_1 = outputs[1].get_size();
+        for (size_t i = 0lu; i < el_num_1; i++) {
+            out_data_1[i] = in_data_1[i];
+        }
+
+        return true;
+    }
+
+    bool evaluate(ov::TensorVector& output_values,
+                  const ov::TensorVector& input_values,
+                  const ov::EvaluationContext& evaluationContext) const override {
+        return evaluate(output_values, input_values);
+    }
+
+    bool has_evaluate() const override { return true; }
+};
+
+class CustomOpStringU8 : public ov::op::Op {
+public:
+    OPENVINO_OP("CustomOpStringU8");
+
+    CustomOpStringU8() = default;
+    CustomOpStringU8(const ov::OutputVector& args) : Op(args) {
+        constructor_validate_and_infer_types();
+    }
+
+    void validate_and_infer_types() override {
+        const auto& inputs_count = input_values().size();
+        OPENVINO_ASSERT(inputs_count == 1, "Input count must be 1, Got: ", inputs_count);
+        OPENVINO_ASSERT(get_input_element_type(0) == ov::element::Type_t::string, "The input must be string.");
+
+        set_output_size(1);
+        set_output_type(0, ov::element::Type_t::u8, get_input_partial_shape(0));
+    }
+
+    std::shared_ptr<ov::Node> clone_with_new_inputs(const ov::OutputVector& new_args) const override {
+        OPENVINO_ASSERT(new_args.size() == 1, "Incorrect number of new arguments: ", new_args.size(), ". 1 is expected.");
+        return std::make_shared<CustomOpStringU8>(new_args);
+    }
+
+    bool evaluate(ov::TensorVector& outputs, const ov::TensorVector& inputs) const override {
+        for (size_t i = 0lu; i < inputs.size(); i++) {
+            OPENVINO_ASSERT(inputs[i].get_shape().size() == static_cast<size_t>(get_input_partial_shape(i).rank().get_length()),
+                "Invalid input shape rank: ", inputs[i].get_shape().size());
+        }
+        for (size_t i = 0lu; i < outputs.size(); i++) {
+            OPENVINO_ASSERT(outputs[i].get_shape().size() == static_cast<size_t>(get_output_partial_shape(i).rank().get_length()),
+                "Invalid outputs shape rank: ", outputs[i].get_shape().size());
+        }
+
+        auto in_data_0 = inputs[0].data<ov::element_type_traits<ov::element::string>::value_type>();
+        auto out_data_0 = outputs[0].data<ov::element_type_traits<ov::element::u8>::value_type>();
+
+        const auto el_num_0 = outputs[0].get_size();
+        for (size_t i = 0lu; i < el_num_0; i++) {
+            if (in_data_0[i].empty()) {
+                out_data_0[i] = '_';
+            } else {
+                out_data_0[i] = in_data_0[i][0];
+            }
+        }
+
+        return true;
+    }
+
+    bool has_evaluate() const override { return true; }
+    bool visit_attributes(ov::AttributeVisitor& visitor) override { return true; }
+};
+
+class CustomOpStringCPUTest : public testing::WithParamInterface<CustomOpStringCPUTestParams>,
+                                  virtual public SubgraphBaseTest,
+                                  public CPUTestsBase {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<CustomOpStringCPUTestParams>& obj) {
+        ElementType in_type;
+        InputShape inputShape;
+        std::tie(in_type, inputShape) = obj.param;
+
+        std::ostringstream result;
+        result << "IS=" << inputShape << "_";
+        result << "Prc=" << in_type;
+        return result.str();
+    }
+
+protected:
+    void SetUp() override {
+        targetDevice = utils::DEVICE_CPU;
+
+        ElementType in_type;
+        InputShape inputShape;
+        std::tie(in_type, inputShape) = this->GetParam();
+
+        init_input_shapes({inputShape});
+
+        auto in_0 = std::make_shared<ov::op::v0::Parameter>(in_type, inputDynamicShapes[0]);
+        auto in_1 = std::make_shared<ov::op::v0::Constant>(utils::create_and_fill_tensor(in_type, { 1, 3, 5 }));
+        ov::OutputVector param_outs_0({ in_0, in_1 });
+        auto str_str_op = std::make_shared<CustomOpStringString>(param_outs_0);
+        ov::OutputVector param_outs_1({ str_str_op->output(0) });
+        auto str_u8_op_0 = std::make_shared<CustomOpStringU8>(param_outs_1);
+        ov::OutputVector param_outs_2({ in_0 });
+        auto str_u8_op_1 = std::make_shared<CustomOpStringU8>(param_outs_2);
+        ov::OutputVector param_outs_3({ in_1 });
+        auto str_u8_op_2 = std::make_shared<CustomOpStringU8>(param_outs_3);
+        auto btw_not_op = std::make_shared<ov::op::v13::BitwiseNot>(str_u8_op_0->output(0));
+
+        ov::ParameterVector input_params{in_0};
+        ov::ResultVector results{std::make_shared<ov::op::v0::Result>(btw_not_op->output(0)),
+                                 std::make_shared<ov::op::v0::Result>(str_str_op->output(1)),
+                                 std::make_shared<ov::op::v0::Result>(str_u8_op_1->output(0)),
+                                 std::make_shared<ov::op::v0::Result>(str_u8_op_2->output(0))};
+        function = std::make_shared<ov::Model>(results, input_params, "CustomOpStringString");
+    }
+
+    void generate_inputs(const std::vector<ov::Shape>& targetInputStaticShapes) override {
+        inputs.clear();
+        const auto& funcInputs = function->inputs();
+        for (size_t i = 0lu; i < funcInputs.size(); ++i) {
+            const auto& funcInput = funcInputs[i];
+            auto tensor = utils::create_and_fill_tensor(funcInput.get_element_type(), targetInputStaticShapes[i]);
+
+            inputs.insert({funcInput.get_node_shared_ptr(), tensor});
+        }
+    }
+
+    void compare(const std::vector<ov::Tensor>& expected, const std::vector<ov::Tensor>& actual) override {
+        ASSERT_EQ(expected.size(), actual.size());
+        ASSERT_EQ(expected.size(), function->get_results().size());
+
+        auto expected_data_0 = expected[0].data<ov::element_type_traits<ov::element::u8>::value_type>();
+        auto actual_data_0 = actual[0].data<ov::element_type_traits<ov::element::u8>::value_type>();
+        const auto size_0 = expected[0].get_size();
+
+        for (size_t i = 0lu; i < size_0; i++) {
+            OPENVINO_ASSERT(expected_data_0[i] == actual_data_0[i], "At index ", i,
+                " expected: '", expected_data_0[i], "' actual: '", actual_data_0[i], "'");
+        }
+
+        auto expected_data_1 = expected[1].data<ov::element_type_traits<ov::element::string>::value_type>();
+        auto actual_data_1 = actual[1].data<ov::element_type_traits<ov::element::string>::value_type>();
+        const auto size_1 = expected[1].get_size();
+
+        for (size_t i = 0lu; i < size_1; i++) {
+            OPENVINO_ASSERT(expected_data_1[i] == actual_data_1[i], "At index ", i,
+                " expected: '", expected_data_1[i], "' actual: '", actual_data_1[i], "'");
+        }
+    }
+};
+
+TEST_P(CustomOpStringCPUTest, CompareWithRefs) {
+    run();
+}
+
+const std::vector<InputShape> inputShapes = {
+    {{}, {{2, 5}}},
+    {{}, {{17, 9}}},
+    {{-1, -1}, {{1, 3}, {5, 17}, {99, 51}}},
+    {{}, {{}}}
+};
+
+INSTANTIATE_TEST_SUITE_P(smoke_CustomOp,
+                         CustomOpStringCPUTest,
+                         ::testing::Combine(::testing::Values(ElementType::string), ::testing::ValuesIn(inputShapes)),
+                         CustomOpStringCPUTest::getTestCaseName);
+
+} // namespace SubgraphTestsDefinitions
diff --git a/src/tests/test_utils/common_test_utils/include/common_test_utils/data_utils.hpp b/src/tests/test_utils/common_test_utils/include/common_test_utils/data_utils.hpp
index 3b876a530cd..cf0e0ebe299 100644
--- a/src/tests/test_utils/common_test_utils/include/common_test_utils/data_utils.hpp
+++ b/src/tests/test_utils/common_test_utils/include/common_test_utils/data_utils.hpp
@@ -465,6 +465,12 @@ void inline fill_data_random<InferenceEngine::Precision::BF16>(InferenceEngine::
 }
 OPENVINO_SUPPRESS_DEPRECATED_END
 
+void fill_random_string(std::string* dst,
+                        const size_t size,
+                        const size_t len_range = 10lu,
+                        const size_t start_from = 0lu,
+                        const int seed = 1);
+
 template <typename T>
 typename std::enable_if<std::is_signed<T>::value, T>::type inline ie_abs(const T& val) {
     return std::abs(val);
diff --git a/src/tests/test_utils/common_test_utils/src/data_utils.cpp b/src/tests/test_utils/common_test_utils/src/data_utils.cpp
index ee1eb532c87..7f9d15306fa 100644
--- a/src/tests/test_utils/common_test_utils/src/data_utils.cpp
+++ b/src/tests/test_utils/common_test_utils/src/data_utils.cpp
@@ -578,6 +578,27 @@ void fill_tensor_random(ov::Tensor& tensor,
 #undef CASE_FLOAT
 }
 
+void fill_random_string(std::string* dst,
+                        const size_t size,
+                        const size_t len_range,
+                        const size_t start_from,
+                        const int seed) {
+    static const int32_t char_range = 128;
+    testing::internal::Random random_len(seed);
+    random_len.Generate(len_range);
+    testing::internal::Random random_char(seed);
+    random_char.Generate(char_range);
+
+    for (size_t i = 0lu; i < size; i++) {
+        const auto len = start_from + static_cast<size_t>(random_len.Generate(len_range));
+        auto& str = dst[i];
+        str.resize(len);
+        for (size_t j = 0lu; j < len; j++) {
+            str[j] = static_cast<char>(random_len.Generate(char_range));
+        }
+    }
+}
+
 }  // namespace utils
 }  // namespace test
 }  // namespace ov
diff --git a/src/tests/test_utils/common_test_utils/src/ov_tensor_utils.cpp b/src/tests/test_utils/common_test_utils/src/ov_tensor_utils.cpp
index b39a53bb296..8f8a503af9d 100644
--- a/src/tests/test_utils/common_test_utils/src/ov_tensor_utils.cpp
+++ b/src/tests/test_utils/common_test_utils/src/ov_tensor_utils.cpp
@@ -51,6 +51,13 @@ ov::Tensor create_and_fill_tensor(const ov::element::Type element_type,
                          inGenData.resolution,
                          inGenData.seed);
         break;
+    case ov::element::Type_t::string:
+        fill_random_string(static_cast<std::string*>(tensor.data()),
+                           tensor.get_size(),
+                           inGenData.range,
+                           inGenData.start_from,
+                           inGenData.seed);
+        break;
     default:
         OPENVINO_THROW("Unsupported element type: ", element_type);
     }