diff --git a/frameworks/native/neural_network_core/backend_manager.cpp b/frameworks/native/neural_network_core/backend_manager.cpp
index 699df8d504a6a112ba833d590b030669cf2c759a..b1c6f11760aa2bf15aa32b9406401493ca13d8cb 100644
--- a/frameworks/native/neural_network_core/backend_manager.cpp
+++ b/frameworks/native/neural_network_core/backend_manager.cpp
@@ -34,7 +34,6 @@ BackendManager& BackendManager::GetInstance()
     if (dlopen("libneural_network_runtime.so", RTLD_NOLOAD) != nullptr) {
         // if libneural_network_runtime_ext.so not loaded, try to dlopen it
         if (dlopen("libneural_network_runtime_ext.so", RTLD_NOLOAD) == nullptr) {
-            LOGI("dlopen libneural_network_runtime_ext.so.");
             void* libHandle = dlopen("libneural_network_runtime_ext.so", RTLD_NOW | RTLD_GLOBAL);
             if (libHandle == nullptr) {
                 LOGW("Failed to dlopen libneural_network_runtime_ext.so.");
@@ -142,7 +141,6 @@ OH_NN_ReturnCode BackendManager::RegisterBackend(
 
 void BackendManager::RemoveBackend(const std::string& backendName)
 {
-    LOGI("[RemoveBackend] start remove backend for %{public}s.", backendName.c_str());
     const std::lock_guard<std::mutex> lock(m_mtx);
     if (m_backendIDGroup.find(backendName) == m_backendIDGroup.end()) {
         LOGI("[RemoveBackend] No need to remove backend for %{public}s.", backendName.c_str());
@@ -161,7 +159,6 @@ void BackendManager::RemoveBackend(const std::string& backendName)
         if (m_backendNames.find(backendID) != m_backendNames.end()) {
             m_backendNames.erase(backendID);
         }
-        LOGI("[RemoveBackend] remove backendID[%{public}zu] for %{public}s success.", backendID, backendName.c_str());
     }
     m_backendIDGroup.erase(backendName);
 }
diff --git a/frameworks/native/neural_network_core/neural_network_core.cpp b/frameworks/native/neural_network_core/neural_network_core.cpp
index e5cc6b97bda16a5e19e7dd7bf729d6ae730ee3cc..b55a08be15c8272871f1709a6b546946b7e82ca1 100644
--- a/frameworks/native/neural_network_core/neural_network_core.cpp
+++ b/frameworks/native/neural_network_core/neural_network_core.cpp
@@ -544,7 +544,6 @@ OH_NN_ReturnCode AuthenticateModel(const Compilation* compilation, bool &isExcee
     }
 
     if (!isExceedRamLimit) {
-        LOGI("Model accupy memory less then limit, no need authenticating.");
         return OH_NN_SUCCESS; // If model ram is less than max limit, no need authenticating.
     }
 
@@ -609,7 +608,6 @@ OH_NN_ReturnCode Authentication(Compilation** compilation, bool &isExceedRamLimi
         return ret;
     }
 
-    LOGI("Authentication success.");
     return OH_NN_SUCCESS;
 }
 
@@ -617,10 +615,7 @@ namespace {
 OH_NN_ReturnCode GetNnrtModelId(Compilation* compilationImpl, NNRtServiceApi& nnrtService)
 {
     std::string modelName;
-    OH_NN_ReturnCode retCode = compilationImpl->compiler->GetModelName(modelName);
-    if (retCode != OH_NN_SUCCESS) {
-        LOGW("GetModelName is failed.");
-    }
+    compilationImpl->compiler->GetModelName(modelName);
 
     if (compilationImpl->nnModel != nullptr) {
         compilationImpl->nnrtModelID = nnrtService.GetNNRtModelIDFromCache(compilationImpl->cachePath,
@@ -757,7 +752,6 @@ NNRT_API OH_NN_ReturnCode OH_NNCompilation_Build(OH_NNCompilation *compilation)
     }
 
     std::unordered_map<std::string, std::vector<char>> configs;
-    LOGI("[OH_NNCompilation_Build] model isExceedRamLimit: %{public}d", static_cast<int>(isExceedRamLimit));
 
     std::vector<char> configContents;
     if (isExceedRamLimit) {
@@ -1663,7 +1657,6 @@ OH_NN_ReturnCode UpdateModelLatency(const ExecutorConfig* config, int32_t modelL
         return static_cast<OH_NN_ReturnCode>(ret);
     }
 
-    LOGI("UpdateModelLatency success.");
     return OH_NN_SUCCESS;
 }
 
diff --git a/frameworks/native/neural_network_runtime/nncompiled_cache.cpp b/frameworks/native/neural_network_runtime/nncompiled_cache.cpp
index 5053e52fcf2474d0ee8b34b1c332a9043979ba24..effcab5ad5360e739bc82cafab988521f3b5c48f 100644
--- a/frameworks/native/neural_network_runtime/nncompiled_cache.cpp
+++ b/frameworks/native/neural_network_runtime/nncompiled_cache.cpp
@@ -40,7 +40,6 @@ OH_NN_ReturnCode NNCompiledCache::Save(const std::vector<OHOS::NeuralNetworkRunt
                                        const std::string& cacheDir,
                                        uint32_t version)
 {
-    LOGI("[NNCompiledCache::Save] m_isExceedRamLimit: %{public}d", static_cast<int>(m_isExceedRamLimit));
     if (caches.empty()) {
         LOGE("[NNCompiledCache] Save failed, caches is empty.");
         return OH_NN_INVALID_PARAMETER;
@@ -57,7 +56,6 @@ OH_NN_ReturnCode NNCompiledCache::Save(const std::vector<OHOS::NeuralNetworkRunt
         return ret;
     }
 
-    LOGI("[NNCompiledCache] Save success. %zu caches are saved.", caches.size());
     return OH_NN_SUCCESS;
 }
 
@@ -256,7 +254,6 @@ OH_NN_ReturnCode NNCompiledCache::GenerateCacheModel(const std::vector<OHOS::Neu
     }
     cacheInfo["data"]["opVersion"] = currentOpVersion;
 
-    LOGI("[NNCompiledCache] GenerateCacheModel m_isExceedRamLimit: %{public}d", static_cast<int>(m_isExceedRamLimit));
     cacheInfo["data"]["isExceedRamLimit"] = m_isExceedRamLimit ? 1 : 0;
 
     const size_t dataLength = cacheInfo["data"].dump().length();
diff --git a/frameworks/native/neural_network_runtime/nncompiler.cpp b/frameworks/native/neural_network_runtime/nncompiler.cpp
index ec40f00e2d037745cd27b02905dce5f6e5a50aa5..c27b3131ed83ea7f5c481a183a0b8350d57f542b 100644
--- a/frameworks/native/neural_network_runtime/nncompiler.cpp
+++ b/frameworks/native/neural_network_runtime/nncompiler.cpp
@@ -287,7 +287,6 @@ OH_NN_ReturnCode NNCompiler::CheckModelParameter() const
 {
     // If m_innerModel is not passed, the compiler must be construct from cache, jump check m_innerModel.
     if (m_innerModel == nullptr) {
-        LOGW("[NNCompiler] Restoring from cache not need to check model.");
         return OH_NN_SUCCESS;
     }
 
@@ -309,7 +308,6 @@ OH_NN_ReturnCode NNCompiler::IsOfflineModel(bool& isOfflineModel) const
 {
     // If m_innerModel is not passed, the compiler must be construct from cache, jump check m_innerModel.
     if (m_innerModel == nullptr) {
-        LOGW("[NNCompiler] Restoring from cache not need to judge offline model.");
         return OH_NN_SUCCESS;
     }
 
@@ -456,12 +454,7 @@ OH_NN_ReturnCode NNCompiler::OnlineBuild()
     // cache存在，从cache直接复原prepareModel、input/output TensorDesc
     OH_NN_ReturnCode ret = RestoreFromCacheFile();
     if (ret != OH_NN_SUCCESS) {
-        LOGW("[NNCompiler] cache file is failed, to delete cache file.");
         char path[PATH_MAX];
-        if (realpath(m_cachePath.c_str(), path) == nullptr) {
-            LOGW("[NNCompiledCache] WriteCacheInfo failed, fail to get the real path of cacheDir.");
-        }
-
         std::string cachePath = path;
         std::string cacheInfo = cachePath + "/" + m_extensionConfig.modelName + "cache_info.nncache";
         if (std::filesystem::exists(cacheInfo)) {
@@ -474,7 +467,6 @@ OH_NN_ReturnCode NNCompiler::OnlineBuild()
         return ret;
     }
     if (ret == OH_NN_SUCCESS) {
-        LOGI("[NNCompiler] Build success, restore from cache file.");
         m_isBuild = true;
     }
 
@@ -705,7 +697,6 @@ OH_NN_ReturnCode NNCompiler::RestoreFromCacheFile()
 
     m_inputTensorDescs = inputTensorDescs;
     m_outputTensorDescs = outputTensorDescs;
-    LOGI("[NNCompiler] Restore model cache successfully.");
     return OH_NN_SUCCESS;
 }
 
@@ -730,7 +721,6 @@ OH_NN_ReturnCode NNCompiler::SetExtensionConfig(const std::unordered_map<std::st
             return OH_NN_INVALID_PARAMETER;
         }
         m_extensionConfig.modelName.assign(value.data(), value.data() + value.size());
-        LOGI("[NNCompiler] SetExtensionConfig get model name:%{public}s.", m_extensionConfig.modelName.c_str());
     }
     if (configs.find(EXTENSION_KEY_FM_SHARED) != configs.end()) {
         m_extensionConfig.isNpuFmShared = true;
@@ -748,15 +738,12 @@ OH_NN_ReturnCode NNCompiler::SetExtensionConfig(const std::unordered_map<std::st
         } else {
             m_extensionConfig.isExceedRamLimit = false;
         }
-
-        LOGI("[NNCompiler] SetExtensionConfig isExceedRamLimit enabled.");
     }
     return OH_NN_SUCCESS;
 }
 
 OH_NN_ReturnCode NNCompiler::SetOptions(const std::vector<std::shared_ptr<void>>& options)
 {
-    LOGE("[NNCompiler] SetOptions is not supported for NN compiler currently.");
     return OH_NN_UNSUPPORTED;
 }