diff --git a/paddle/fluid/inference/tensorrt/convert/range_op.cc b/paddle/fluid/inference/tensorrt/convert/range_op.cc
index 4e6847f6c4a656..9b777c9a98cdf6 100644
--- a/paddle/fluid/inference/tensorrt/convert/range_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/range_op.cc
@@ -45,11 +45,7 @@ class RangeOpConverter : public OpConverter {
     }
     auto number_tensor = Max(Sub(zero_tensor, quotient_tensor), zero_tensor);
     auto* start1 = engine_->GetITensor(op_desc.Input("Start")[0]);
-#if IS_TRT_VERSION_LT(8000)
-    nvinfer1::Dims start_dims{0, {1}, { nvinfer1::DimensionType::kSPATIAL }};
-#else
     nvinfer1::Dims start_dims{0, {1}};
-#endif
     start1 = Reshape(start1, start_dims);
     layer = TRT_ENGINE_ADD_LAYER(
         engine_, Fill, nvinfer1::Dims{}, nvinfer1::FillOperation::kLINSPACE);
diff --git a/paddle/fluid/inference/tensorrt/convert/test_custom_op_plugin.h b/paddle/fluid/inference/tensorrt/convert/test_custom_op_plugin.h
index adb41528bae004..d7e43798a92190 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_custom_op_plugin.h
+++ b/paddle/fluid/inference/tensorrt/convert/test_custom_op_plugin.h
@@ -83,15 +83,9 @@ class custom_op_plugin : public nvinfer1::IPluginV2 {
     return 0;
   }
 
-#if IS_TRT_VERSION_LT(8000)
-  int enqueue(int batch_size,
-              const void* const* inputs,
-              void** outputs,
-#else
   int enqueue(int batch_size,
               const void* const* inputs,
               void* const* outputs,
-#endif
               void* workspace,
               cudaStream_t stream) noexcept override {
     return 0;
diff --git a/paddle/fluid/inference/tensorrt/engine.cc b/paddle/fluid/inference/tensorrt/engine.cc
index 725bd4d4cb2fb5..e7a085c523a064 100644
--- a/paddle/fluid/inference/tensorrt/engine.cc
+++ b/paddle/fluid/inference/tensorrt/engine.cc
@@ -326,20 +326,6 @@ void TensorRTEngine::FreezeNetwork() {
     LOG(INFO) << "Run Paddle-TRT Dynamic Shape mode.";
     for (int i = 0; i < max_profile_num_; i++) {
       for (auto &input : min_input_shape()) {
-#if IS_TRT_VERSION_LT(7100)
-        // trt6/trt7011 will check all_of input > 0
-        if (!(std::all_of(input.second.begin(),
-                          input.second.end(),
-                          [](int x) { return x > 0; }) &&
-              std::all_of(max_input_shape()[input.first].begin(),
-                          max_input_shape()[input.first].end(),
-                          [](int x) { return x > 0; }) &&
-              std::all_of(optim_input_shape()[input.first].begin(),
-                          optim_input_shape()[input.first].end(),
-                          [](int x) { return x > 0; }))) {
-          continue;
-        }
-#endif
         VLOG(4) << "TRT dynamic_shape set " << input.first
                 << " min: " << Vec2Str(input.second)
                 << ", max: " << Vec2Str(max_input_shape()[input.first])
@@ -419,10 +405,6 @@ void TensorRTEngine::FreezeNetwork() {
   }
 #endif
 
-#if IS_TRT_VERSION_LT(8000)
-  infer_engine_.reset(infer_builder_->buildEngineWithConfig(
-      *network(), *infer_builder_config_));
-#else
   ihost_memory_.reset(infer_builder_->buildSerializedNetwork(
       *network(), *infer_builder_config_));
   PADDLE_ENFORCE_NOT_NULL(
@@ -439,7 +421,6 @@ void TensorRTEngine::FreezeNetwork() {
 
   infer_engine_.reset(infer_runtime_->deserializeCudaEngine(
       ihost_memory_->data(), ihost_memory_->size()));
-#endif
 
   PADDLE_ENFORCE_NOT_NULL(
       infer_engine_,
diff --git a/paddle/fluid/inference/tensorrt/engine.h b/paddle/fluid/inference/tensorrt/engine.h
index 02486c57cb2403..0d07c33a2f6d17 100644
--- a/paddle/fluid/inference/tensorrt/engine.h
+++ b/paddle/fluid/inference/tensorrt/engine.h
@@ -256,14 +256,10 @@ class TensorRTEngine {
         infer_engine_,
         common::errors::InvalidArgument(
             "The TensorRT engine must be built first before serialization"));
-#if IS_TRT_VERSION_LT(8000)
-    ihost_memory_.reset(infer_engine_->serialize());
-#else
     PADDLE_ENFORCE_NOT_NULL(
         ihost_memory_,
         common::errors::InvalidArgument(
             "TensorRT >= 8.0 requires that buildSerializedNetwork is called"));
-#endif
     return ihost_memory_.get();
   }
 
diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
index 83891ff0354699..0be02840e80935 100644
--- a/paddle/fluid/inference/tensorrt/op_teller.cc
+++ b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -887,10 +887,6 @@ struct SimpleOpTypeSetTeller : public Teller {
     }
 
     if (op_type == "bilinear_interp_v2") {
-      // trt 7011 result in test_solov2_trt_fp32.py TRT fp32 diff
-#if IS_TRT_VERSION_LT(7100)
-      return false;
-#endif
       std::vector<std::string> attrs{"data_layout",
                                      "interp_method",
                                      "align_corners",
@@ -1010,9 +1006,6 @@ struct SimpleOpTypeSetTeller : public Teller {
       }
     }
     if (op_type == "linear_interp_v2") {
-#if IS_TRT_VERSION_LT(7100)
-      return false;
-#endif
       std::vector<std::string> attrs{"data_layout",
                                      "interp_method",
                                      "align_corners",
@@ -1670,13 +1663,6 @@ struct SimpleOpTypeSetTeller : public Teller {
                 << desc.Output("Out").size();
         return false;
       }
-
-#if IS_TRT_VERSION_LT(7000)
-      if (desc.HasAttr("approximate")) {
-        VLOG(3) << "approximate gelu op needs TensorRT 7.0 and after";
-        if (PADDLE_GET_CONST(bool, desc.GetAttr("approximate"))) return false;
-      }
-#endif
     }
 
     if (op_type == "layer_norm") {
@@ -2154,8 +2140,7 @@ struct SimpleOpTypeSetTeller : public Teller {
           return false;
         }
       } else {
-#if (IS_TRT_VERSION_GE(8000) && IS_TRT_VERSION_LT(8100)) || \
-    (IS_TRT_VERSION_LT(7200))
+#if (IS_TRT_VERSION_GE(8000) && IS_TRT_VERSION_LT(8100))
         VLOG(3) << "There are some bugs with trt 8.0";
         return false;
 #endif
@@ -2691,15 +2676,6 @@ struct SimpleOpTypeSetTeller : public Teller {
                    "the pass.";
         return false;
       }
-
-#if IS_TRT_VERSION_LT(8000)
-      auto x_var_name = desc.Input("X")[0];
-      auto* x_var_desc = block->FindVarRecursive(x_var_name);
-      const auto x_shape = x_var_desc->GetShape();
-      if (x_shape.size() == 0) {
-        return false;  // not supported 0 dim.
-      }
-#endif
     }
 
     if (op_type == "grid_sampler") {