diff --git a/paddle/cinn/hlir/dialect/operator/transforms/CMakeLists.txt b/paddle/cinn/hlir/dialect/operator/transforms/CMakeLists.txt
index dbe7f3c40adad6..9b57f4f14edeaf 100644
--- a/paddle/cinn/hlir/dialect/operator/transforms/CMakeLists.txt
+++ b/paddle/cinn/hlir/dialect/operator/transforms/CMakeLists.txt
@@ -38,4 +38,13 @@ if(NOT CINN_ONLY)
     cinn_op_dialect
     op_dialect_vjp)
 
+  cinn_cc_library(
+    split_generate_shape_into_shape_ops_pass
+    SRCS
+    split_generate_shape_into_shape_ops_pass.cc
+    DEPS
+    pir
+    cinn_op_dialect
+    op_dialect_vjp)
+
 endif()
diff --git a/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.cc b/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.cc
new file mode 100644
index 00000000000000..cec66f7c70e2e1
--- /dev/null
+++ b/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.cc
@@ -0,0 +1,368 @@
+// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.h"
+
+#include "paddle/cinn/common/dim_expr_simplify.h"
+#include "paddle/cinn/hlir/dialect/operator/ir/cinn_op.h"
+#include "paddle/cinn/hlir/dialect/operator/ir/generate_shape_util.h"
+#include "paddle/cinn/hlir/dialect/operator/ir/manual_op.h"
+#include "paddle/cinn/hlir/framework/pir/utils.h"
+#include "paddle/common/ddim.h"
+#include "paddle/fluid/pir/dialect/operator/ir/manual_op.h"
+#include "paddle/fluid/pir/dialect/operator/ir/op_attribute.h"
+#include "paddle/fluid/pir/dialect/operator/ir/op_type.h"
+#include "paddle/fluid/pir/dialect/operator/ir/pd_op.h"
+#include "paddle/fluid/pir/drr/api/match_context.h"
+#include "paddle/pir/core/builtin_dialect.h"
+#include "paddle/pir/dialect/shape/utils/dim_expr.h"
+#include "paddle/pir/pass/pass.h"
+#include "paddle/pir/pattern_rewrite/pattern_applicator.h"
+#include "paddle/pir/pattern_rewrite/pattern_match.h"
+#include "paddle/pir/pattern_rewrite/pattern_rewrite_driver.h"
+
+namespace cinn {
+namespace dialect {
+namespace ir {
+
+namespace {
+
+struct TensorDimInShape {
+  pir::Value value;
+  int axis;
+};
+
+struct TensorDimInData {
+  pir::Value value;
+  int axis;
+};
+
+using TensorDim = std::variant<TensorDimInShape, TensorDimInData>;
+
+using TensorDim4SymbolNameT =
+    std::function<std::optional<TensorDim>(const std::string& symbol_name)>;
+
+struct CachedDimExprToValueConverter {
+  CachedDimExprToValueConverter(
+      const TensorDim4SymbolNameT& TensorDim4SymbolNameVal,
+      pir::PatternRewriter* rewriter_val)
+      : TensorDim4SymbolName(TensorDim4SymbolNameVal), rewriter(rewriter_val) {}
+
+  TensorDim4SymbolNameT TensorDim4SymbolName;
+  pir::PatternRewriter* rewriter;
+
+  // TODO(): Refactor to cached version if std::hash<symbol::DimExpr>() is
+  // ready. std::unordered_map<symbol::DimExpr, pir::Value>
+  // symbol_names2cached_value_;
+
+  pir::Value ConvertToValue(const symbol::DimExpr& dim_expr) {
+    // TODO():  cache the returned value if std::hash<symbol::DimExpr>() is
+    // ready
+    return std::visit(
+        [&](const auto& impl) { return ConvertToValueImpl(impl); },
+        dim_expr.variant());
+  }
+
+  pir::Value GetInputShapeByInputTensor(pir::Value input_tensor) {
+    auto iter = tensor2shape_.find(input_tensor);
+    if (iter == tensor2shape_.end()) {
+      pir::Value input_shape =
+          rewriter->Build<paddle::dialect::ShapeOp>(input_tensor).out();
+      iter = tensor2shape_.emplace(input_tensor, input_shape).first;
+    }
+    return iter->second;
+  }
+
+ private:
+  std::unordered_map<pir::Value /*input tensor*/,
+                     pir::Value /*input shape tensor*/>
+      tensor2shape_;
+
+  pir::Value ConvertToValueImpl(int64_t dim_expr) {
+    return rewriter
+        ->Build<paddle::dialect::FullIntArrayOp>(std::vector{dim_expr},
+                                                 phi::DataType::INT64)
+        .out();
+  }
+
+  pir::Value ConvertToValueImpl(const std::string& symbol_name) {
+    const auto& tensor_dim = TensorDim4SymbolName(symbol_name);
+    PADDLE_ENFORCE(
+        tensor_dim.has_value(),
+        phi::errors::PreconditionNotMet(
+            "symbol [%s] are not bound to any input of generate_shape op",
+            symbol_name));
+    return std::visit(
+        [&](const auto& impl) { return ConvertTensorDimToValue(impl); },
+        tensor_dim.value());
+  }
+
+  pir::Value ConvertTensorDimToValue(const TensorDimInShape& tensor_dim) {
+    pir::Value input_shape = GetInputShapeByInputTensor(tensor_dim.value);
+    return ConvertTensorDimToValue(
+        TensorDimInData{.value = input_shape, .axis = tensor_dim.axis});
+  }
+
+  pir::Value ConvertTensorDimToValue(const TensorDimInData& tensor_dim) {
+    return rewriter
+        ->Build<paddle::dialect::SliceOp>(
+            tensor_dim.value,
+            std::vector<int64_t>{0LL},
+            std::vector<int64_t>{tensor_dim.axis},
+            std::vector<int64_t>{tensor_dim.axis + 1},
+            std::vector<int64_t>{},
+            std::vector<int64_t>{})
+        .out();
+  }
+
+  pir::Value ConvertToValueImpl(
+      const symbol::Negative<symbol::DimExpr>& dim_expr) {
+    LOG(FATAL) << "Dead code. This logical should handled by "
+                  "ConvertToValueImpl(symbol::Add<symbol::DimExpr>)";
+  }
+
+  pir::Value ConvertToValueImpl(
+      const symbol::Reciprocal<symbol::DimExpr>& dim_expr) {
+    LOG(FATAL) << "Dead code. This logical should handled by "
+                  "ConvertToValueImpl(symbol::Mul<symbol::DimExpr>)";
+  }
+
+  pir::Value ConvertToValueImpl(const symbol::Add<symbol::DimExpr>& dim_expr) {
+    const auto& [operands] = dim_expr;
+    CHECK_GT(operands->size(), 0);
+    pir::Value acc = ConvertToValue(operands->at(0));
+    for (int i = 1; i < operands->size(); ++i) {
+      if (operands->at(i).isa<symbol::Negative<symbol::DimExpr>>()) {
+        const auto& [operand] =
+            *operands->at(i).dyn_cast<symbol::Negative<symbol::DimExpr>>();
+        pir::Value operand_value = ConvertToValue(operand);
+        acc = rewriter->Build<paddle::dialect::SubtractOp>(acc, operand_value)
+                  .out();
+      } else {
+        pir::Value operand_value = ConvertToValue(operands->at(i));
+        acc = rewriter->Build<paddle::dialect::AddOp>(acc, operand_value).out();
+      }
+    }
+    return acc;
+  }
+
+  pir::Value ConvertToValueImpl(const symbol::Mul<symbol::DimExpr>& dim_expr) {
+    const auto& [operands] = dim_expr;
+    CHECK_GT(operands->size(), 0);
+    pir::Value prod = ConvertToValue(operands->at(0));
+    for (int i = 1; i < operands->size(); ++i) {
+      if (operands->at(i).isa<symbol::Reciprocal<symbol::DimExpr>>()) {
+        const auto& [operand] =
+            *operands->at(i).dyn_cast<symbol::Negative<symbol::DimExpr>>();
+        pir::Value operand_value = ConvertToValue(operand);
+        prod = rewriter->Build<paddle::dialect::DivideOp>(prod, operand_value)
+                   .out();
+      } else {
+        pir::Value operand_value = ConvertToValue(operands->at(i));
+        prod = rewriter->Build<paddle::dialect::MultiplyOp>(prod, operand_value)
+                   .out();
+      }
+    }
+    return prod;
+  }
+
+  pir::Value ConvertToValueImpl(const symbol::Max<symbol::DimExpr>& dim_expr) {
+    const auto& [operands] = dim_expr;
+    CHECK_GT(operands->size(), 0);
+    pir::Value max = ConvertToValue(operands->at(0));
+    for (int i = 1; i < operands->size(); ++i) {
+      pir::Value operand_value = ConvertToValue(operands->at(i));
+      max = rewriter->Build<paddle::dialect::MaxOp>(max, operand_value).out();
+    }
+    return max;
+  }
+
+  pir::Value ConvertToValueImpl(const symbol::Min<symbol::DimExpr>& dim_expr) {
+    const auto& [operands] = dim_expr;
+    CHECK_GT(operands->size(), 0);
+    pir::Value min = ConvertToValue(operands->at(0));
+    for (int i = 1; i < operands->size(); ++i) {
+      pir::Value operand_value = ConvertToValue(operands->at(i));
+      min = rewriter->Build<paddle::dialect::MinOp>(min, operand_value).out();
+    }
+    return min;
+  }
+
+  pir::Value ConvertToValueImpl(
+      const symbol::Broadcast<symbol::DimExpr>& dim_expr) {
+    const auto& [operands] = dim_expr;
+    CHECK_GT(operands->size(), 0);
+    pir::Value broadcasted = ConvertToValue(operands->at(0));
+    for (int i = 1; i < operands->size(); ++i) {
+      pir::Value operand_value = ConvertToValue(operands->at(i));
+      broadcasted = rewriter
+                        ->Build<paddle::dialect::ShapeBroadcastOp>(
+                            broadcasted, operand_value)
+                        .out();
+    }
+    return broadcasted;
+  }
+};
+
+}  // namespace
+
+class SplitGenerateShapeIntoShapeOps
+    : public pir::OpRewritePattern<cinn::dialect::GenerateShapeOp> {
+ public:
+  using pir::OpRewritePattern<cinn::dialect::GenerateShapeOp>::OpRewritePattern;
+
+  bool MatchAndRewrite(cinn::dialect::GenerateShapeOp op,
+                       pir::PatternRewriter& rewriter) const override {
+    std::optional<pir::Value> out_replacement =
+        GetOutReplacement(op, &rewriter);
+    if (!out_replacement.has_value()) return false;
+    rewriter.ReplaceAllUsesWith(op->result(0), out_replacement.value());
+    return true;
+  }
+
+  std::optional<pir::Value> GetOutReplacement(
+      cinn::dialect::GenerateShapeOp op, pir::PatternRewriter* rewriter) const {
+    std::vector<symbol::DimExpr> dim_exprs = GetOutDimExprs(op);
+    TensorDim4SymbolNameT TensorDim4SymbolName =
+        MakeGetterTensorDim4SymbolName(op);
+    if (!TensorDim4SymbolName) return std::nullopt;
+    CachedDimExprToValueConverter converter{TensorDim4SymbolName, rewriter};
+    return GetValueOfRewritedOps(dim_exprs, &converter);
+  }
+
+  TensorDim4SymbolNameT MakeGetterTensorDim4SymbolName(
+      cinn::dialect::GenerateShapeOp op) const {
+    std::unordered_map<std::string, TensorDim> symbol_name2tenso_dim{};
+    const auto& attr_map = op->attributes();
+    const auto& iter = attr_map.find("symbol_bindings");
+    PADDLE_ENFORCE((iter != attr_map.end()),
+                   phi::errors::PreconditionNotMet(
+                       "attr symbol_bindings MUST in attribute map for [%s] op",
+                       op->name()));
+    pir::Attribute attr = iter->second;
+    auto* Convert =
+        &cinn::dialect::GenerateShapeOp::ConvertAttributeToSymbolBindings;
+    const auto& symbol_bindings = Convert(attr);
+    PADDLE_ENFORCE(
+        symbol_bindings.has_value(),
+        phi::errors::PreconditionNotMet("attr symbol_bindings in op [%s] can "
+                                        "not be converted to symbol bindings",
+                                        op->name()));
+    for (const auto& symbol_binding : symbol_bindings.value()) {
+      InsertSymbolBinding(op, symbol_binding, &symbol_name2tenso_dim);
+    }
+    return [map = std::move(symbol_name2tenso_dim)](
+               const std::string& symbol_name) -> std::optional<TensorDim> {
+      auto iter = map.find(symbol_name);
+      if (iter == map.end()) return std::nullopt;
+      return iter->second;
+    };
+  }
+
+  void InsertSymbolBinding(
+      cinn::dialect::GenerateShapeOp op,
+      const cinn::dialect::GenerateShapeOp::SymbolBinding& symbol_binding,
+      std::unordered_map<std::string, TensorDim>* symbol_name2tenso_dim) const {
+    return std::visit(
+        [&](const auto& impl) {
+          return InsertSymbolBindingImpl(op, impl, symbol_name2tenso_dim);
+        },
+        symbol_binding);
+  }
+
+  void InsertSymbolBindingImpl(
+      cinn::dialect::GenerateShapeOp op,
+      const cinn::dialect::GenerateShapeOp::DataSymbolBinding& symbol_binding,
+      std::unordered_map<std::string, TensorDim>* symbol_name2tenso_dim) const {
+    (*symbol_name2tenso_dim)[symbol_binding.symbol_name] = TensorDimInData{
+        .value = op.operand_source(symbol_binding.input_tensor_idx),
+        .axis = symbol_binding.input_tensor_dim_idx};
+  }
+
+  void InsertSymbolBindingImpl(
+      cinn::dialect::GenerateShapeOp op,
+      const cinn::dialect::GenerateShapeOp::ShapeSymbolBinding& symbol_binding,
+      std::unordered_map<std::string, TensorDim>* symbol_name2tenso_dim) const {
+    (*symbol_name2tenso_dim)[symbol_binding.symbol_name] = TensorDimInShape{
+        .value = op.operand_source(symbol_binding.input_tensor_idx),
+        .axis = symbol_binding.input_tensor_dim_idx};
+  }
+
+  std::vector<symbol::DimExpr> GetOutDimExprs(
+      cinn::dialect::GenerateShapeOp op) const {
+    const auto& attr_map = op->attributes();
+    const auto& iter = attr_map.find("output_dim_exprs");
+    PADDLE_ENFORCE(
+        (iter != attr_map.end()),
+        phi::errors::PreconditionNotMet(
+            "attr output_dim_exprs MUST in attribute map for [%s] op",
+            op->name()));
+    pir::Attribute output_dim_exprs_attr = iter->second;
+    PADDLE_ENFORCE(
+        output_dim_exprs_attr.isa<pir::ArrayAttribute>(),
+        phi::errors::PreconditionNotMet(
+            "attr output_dim_exprs for [%s] op must be an pir::ArrayAttribute",
+            op->name()));
+    std::vector<symbol::DimExpr> ret{};
+    const auto& output_dim_exprs =
+        output_dim_exprs_attr.dyn_cast<pir::ArrayAttribute>();
+    for (int i = 0; i < output_dim_exprs.size(); ++i) {
+      const auto& attr = output_dim_exprs.at(i);
+      const auto& opt_dim_expr = cinn::dialect::ConvertAttributeToDimExpr(attr);
+      CHECK(opt_dim_expr.has_value());
+      ret.emplace_back(opt_dim_expr.value());
+    }
+    return ret;
+  }
+
+  pir::Value GetValueOfRewritedOps(
+      const std::vector<symbol::DimExpr>& dim_exprs,
+      CachedDimExprToValueConverter* converter) const {
+    const std::vector<pir::Value>& values_from_dim_exprs =
+        GetValuesOfRewritedOps(dim_exprs, converter);
+    return converter->rewriter->Build<pir::CombineOp>(values_from_dim_exprs)
+        .out();
+  }
+
+  std::vector<pir::Value> GetValuesOfRewritedOps(
+      const std::vector<symbol::DimExpr>& dim_exprs,
+      CachedDimExprToValueConverter* converter) const {
+    std::vector<pir::Value> ret;
+    for (const auto& dim_expr : dim_exprs) {
+      const auto& simplified = cinn::common::SimplifyDimExpr(dim_expr);
+      pir::Value value = converter->ConvertToValue(simplified);
+      ret.push_back(value);
+    }
+    return ret;
+  }
+};
+
+SplitGenerateShapeIntoShapeOpsPass::SplitGenerateShapeIntoShapeOpsPass()
+    : pir::PatternRewritePass("split_generate_shape_into_shape_ops_pass", 1) {}
+
+pir::RewritePatternSet SplitGenerateShapeIntoShapeOpsPass::InitializePatterns(
+    pir::IrContext* context) {
+  pir::RewritePatternSet ps(context);
+  // elementwise ops
+  ps.Add<SplitGenerateShapeIntoShapeOps>(context);
+  return ps;
+}
+
+bool SplitGenerateShapeIntoShapeOpsPass::CanApplyOn(pir::Operation* op) const {
+  return op->isa<pir::ModuleOp>() && op->num_regions() > 0;
+}
+
+}  // namespace ir
+}  // namespace dialect
+}  // namespace cinn
diff --git a/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.h b/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.h
new file mode 100644
index 00000000000000..fe0c3f124cd385
--- /dev/null
+++ b/paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.h
@@ -0,0 +1,35 @@
+// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "paddle/pir/pass/pass.h"
+#include "paddle/pir/pattern_rewrite/frozen_rewrite_pattern_set.h"
+
+namespace cinn {
+namespace dialect {
+namespace ir {
+
+class SplitGenerateShapeIntoShapeOpsPass : public pir::PatternRewritePass {
+ public:
+  SplitGenerateShapeIntoShapeOpsPass();
+
+  pir::RewritePatternSet InitializePatterns(pir::IrContext *context) override;
+
+  bool CanApplyOn(pir::Operation *op) const override;
+};
+
+}  // namespace ir
+}  // namespace dialect
+}  // namespace cinn
diff --git a/paddle/fluid/pybind/CMakeLists.txt b/paddle/fluid/pybind/CMakeLists.txt
index 52eada6c5482ff..08d8a22699e264 100755
--- a/paddle/fluid/pybind/CMakeLists.txt
+++ b/paddle/fluid/pybind/CMakeLists.txt
@@ -51,8 +51,13 @@ set(PYBIND_DEPS
 
 if(WITH_CINN)
   set(PYBIND_DEPS
-      ${PYBIND_DEPS} pir_transforms op_with_group_merge_pass
-      add_broadcast_to_elementwise_pass pd_to_cinn_pass sub_graph_checker)
+      ${PYBIND_DEPS}
+      pir_transforms
+      op_with_group_merge_pass
+      add_broadcast_to_elementwise_pass
+      pd_to_cinn_pass
+      sub_graph_checker
+      split_generate_shape_into_shape_ops_pass)
 endif()
 
 if(WITH_PSCORE)