diff --git a/paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc b/paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
index 18680fe678b5d4d14ccf19fc46bc6ce77d1e3e92..a7f6bc512ffcedf135db6bf285986fb6192be083 100644
--- a/paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
+++ b/paddle/fluid/operators/mkldnn/fc_mkldnn_op.cc
@@ -284,7 +284,13 @@ class FCMKLDNNHandler
 
   std::shared_ptr<dnnl::memory> AcquireWeightsMemoryWithReorder(
       const phi::DenseTensor* weights, const std::vector<float>& scale_data) {
-    const std::string weights_key = this->memory_key_ + "@weights";
+    const std::string weights_base_key = this->memory_key_ + "@weights";
+    std::string weights_key;
+    weights_key.reserve(128);
+    weights_key = phi::funcs::ExtendKeyWithThreadInfoIfNeeded(
+        dev_ctx_,
+        phi::funcs::CreateKey(
+            dev_ctx_, weights_base_key, this->fwd_pd_->weights_desc()));
     auto memory_p = std::static_pointer_cast<dnnl::memory>(
         this->dev_ctx_.GetBlob(weights_key));
 
@@ -410,7 +416,8 @@ class FCMKLDNNKernel : public framework::OpKernel<T_in> {
         phi::funcs::CreateKey(dev_ctx,
                               ctx.InputName("Input"),
                               ctx.InputName("W"),
-                              phi::vectorize(x->dims())));
+                              phi::vectorize(x->dims()),
+                              phi::vectorize(weights->dims())));
 
     auto inner_product_cache =
         std::static_pointer_cast<InnerProductCache>(dev_ctx.GetBlob(cache_key));
diff --git a/paddle/phi/backends/onednn/onednn_helper.h b/paddle/phi/backends/onednn/onednn_helper.h
index 84e36a26ca48714adf8262322bfefee9eb867f22..1d61004b36161ffdc3f16a134a4c2d7ff52dde9c 100644
--- a/paddle/phi/backends/onednn/onednn_helper.h
+++ b/paddle/phi/backends/onednn/onednn_helper.h
@@ -154,6 +154,12 @@ inline void AppendKey(std::string* key, const T& num) {
   key->append(std::to_string(num));
 }
 
+template <>
+inline void AppendKey(std::string* key,
+                      const dnnl::memory::format_kind& format) {
+  key->append(std::to_string(static_cast<int>(format)));
+}
+
 template <>
 inline void AppendKey(std::string* key,
                       const dnnl::memory::format_tag& format) {
@@ -171,6 +177,25 @@ inline void AppendKey(std::string* key, const dnnl::algorithm& algorithm) {
   key->append(std::to_string(static_cast<int>(algorithm)));
 }
 
+template <>
+inline void AppendKey(std::string* key, const dnnl::memory::dims& dims) {
+  for (size_t i = 0; i < dims.size(); i++) {
+    AppendKey(key, static_cast<int64_t>(dims[i]));
+  }
+}
+
+template <>
+inline void AppendKey(std::string* key, const dnnl::memory::desc& md) {
+  AppendKey(key, md.get_dims());
+  AppendKey(key, md.get_data_type());
+  AppendKey(key, md.get_format_kind());
+  AppendKey(key, md.get_inner_blks());
+  AppendKey(key, md.get_inner_idxs());
+  AppendKey(key, md.get_inner_nblks());
+  AppendKey(key, md.get_padded_dims());
+  AppendKey(key, md.get_strides());
+}
+
 template <>
 inline void AppendKey(std::string* key,
                       const dnnl::normalization_flags& flags) {