diff --git a/docs/dev/virtual_machine.rst b/docs/dev/virtual_machine.rst
index 79e1fd94edcd..2791ee71177e 100644
--- a/docs/dev/virtual_machine.rst
+++ b/docs/dev/virtual_machine.rst
@@ -204,7 +204,7 @@ InvokeClosure
 **Arguments**:
 ::
     RegName closure
-    size_t closure_args_num
+    size_t num_closure_args
     RegName* closure_args
 
 Invokes `closure`, consuming the number of arguments declared in the closure's VMFunction.
diff --git a/include/tvm/runtime/vm.h b/include/tvm/runtime/vm.h
index ea1f1b14f023..3e832d49f5bc 100644
--- a/include/tvm/runtime/vm.h
+++ b/include/tvm/runtime/vm.h
@@ -36,6 +36,9 @@ namespace tvm {
 namespace runtime {
 namespace vm {
 
+/*! \brief Magic number for NDArray list file  */
+constexpr uint64_t kTVMNDArrayListMagic = 0xF7E58D4F05049CB7;
+
 /*! \brief A register name. */
 using RegName = int64_t;
 
@@ -103,7 +106,7 @@ struct Instruction {
       /*! \brief The register containing the closure. */
       RegName closure;
       /*! \brief The number of arguments to the closure. */
-      Index closure_args_num;
+      Index num_closure_args;
       /*! \brief The closure arguments as an array. */
       RegName* closure_args;
     };
@@ -115,7 +118,7 @@ struct Instruction {
       /*! \brief The source register for a move operation. */
       RegName from;
     };
-    struct /* Packed Operands */ {
+    struct /* InvokePacked Operands */ {
       /*! \brief The index into the packed function table. */
       Index packed_index;
       /*! \brief The arity of the packed function. */
@@ -149,7 +152,7 @@ struct Instruction {
     };
     struct /* LoadConsti Operands */ {
       /* \brief The index into the constant pool. */
-      size_t val;
+      Index val;
     } load_consti;
     struct /* Jump Operands */ {
       /*! \brief The jump offset. */
@@ -284,7 +287,7 @@ struct Instruction {
    *  \param dst The destination register.
    *  \return The load_constanti instruction.
    */
-  static Instruction LoadConsti(size_t val, RegName dst);
+  static Instruction LoadConsti(Index val, RegName dst);
   /*! \brief Construct a move instruction.
    *  \param src The source register.
    *  \param dst The destination register.
@@ -379,6 +382,8 @@ class VirtualMachine : public runtime::ModuleNode {
     return "VirtualMachine";
   }
 
+  /*! \brief The runtime module/library that contains generated code. */
+  runtime::Module lib;
   /*! \brief The virtual machine's packed function table. */
   std::vector<PackedFunc> packed_funcs;
   /*! \brief The virtual machine's function table. */
@@ -448,16 +453,30 @@ class VirtualMachine : public runtime::ModuleNode {
   void Init(const std::vector<TVMContext>& contexts);
   void Run();
 
+  /*!
+   * \brief Load parameters from the parameter bytearray.
+   * \param params The binary file that contains parameters.
+   */
+  void LoadParams(const std::string& params);
+
   /*! \brief A map from globals (as strings) to their index in the function map.
    */
   std::unordered_map<std::string, Index> global_map;
 
+  /*! \brief A mapping from the packed function (as string) to the index that
+   * corresponds to the position of the `packed_funcs` list.
+   */
+  std::unordered_map<std::string, Index> primitive_map;
+
  private:
   /*! \brief Invoke a global setting up the VM state to execute.
    *
    * This does not begin execution of the VM.
    */
   void InvokeGlobal(const VMFunction& func, const std::vector<Object>& args);
+
+  /*! \brief The parameter name to data mapping. */
+  std::unordered_map<std::string, Object> params_;
 };
 
 }  // namespace vm
diff --git a/python/tvm/relay/__init__.py b/python/tvm/relay/__init__.py
index e94ef411d29d..da14c80b33b4 100644
--- a/python/tvm/relay/__init__.py
+++ b/python/tvm/relay/__init__.py
@@ -34,6 +34,8 @@
 from . import param_dict
 from . import feature
 from .backend import vm
+from .backend import serializer
+from .backend import deserializer
 from .backend import vmobj
 
 # Root operators
diff --git a/python/tvm/relay/backend/deserializer.py b/python/tvm/relay/backend/deserializer.py
new file mode 100644
index 000000000000..fde702b1cd04
--- /dev/null
+++ b/python/tvm/relay/backend/deserializer.py
@@ -0,0 +1,81 @@
+# License .to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+# pylint: disable=invalid-name
+"""
+The Relay Virtual Machine deserializer.
+
+Python interface for deserializing a Relay VM.
+"""
+from tvm import module
+from tvm._ffi.runtime_ctypes import TVMByteArray
+from . import _vm
+from . import vm as rly_vm
+
+def _create_deserializer(code, lib):
+    """Create a deserializer object.
+
+    Parameters
+    ----------
+    code : bytearray
+        The serialized virtual machine code.
+
+    lib : :py:class:`~tvm.module.Module`
+        The serialized runtime module/library that contains the hardware
+        dependent binary code.
+
+    Returns
+    -------
+    ret : Deserializer
+        The created virtual machine deserializer.
+    """
+    if isinstance(code, (bytes, str)):
+        code = bytearray(code)
+    elif not isinstance(code, (bytearray, TVMByteArray)):
+        raise TypeError("vm is expected to be the type of bytearray or " +
+                        "TVMByteArray, but received {}".format(type(code)))
+
+    if not isinstance(lib, module.Module):
+        raise TypeError("lib is expected to be the type of tvm.module.Module" +
+                        ", but received {}".format(type(lib)))
+    return _vm._Deserializer(code, lib)
+
+
+class Deserializer:
+    """Relay VM deserializer.
+
+    Parameters
+    ----------
+    code : bytearray
+        The serialized virtual machine code.
+
+    lib : :py:class:`~tvm.module.Module`
+        The serialized runtime module/library that contains the hardware
+        dependent binary code.
+    """
+    def __init__(self, code, lib):
+        self.mod = _create_deserializer(code, lib)
+        self._deserialize = self.mod["deserialize"]
+
+    def deserialize(self):
+        """Deserialize the serialized bytecode into a Relay VM.
+
+        Returns
+        -------
+        ret : VirtualMachine
+            The deserialized Relay VM.
+        """
+        return rly_vm.VirtualMachine(self._deserialize())
diff --git a/python/tvm/relay/backend/serializer.py b/python/tvm/relay/backend/serializer.py
new file mode 100644
index 000000000000..b45ba9116a15
--- /dev/null
+++ b/python/tvm/relay/backend/serializer.py
@@ -0,0 +1,191 @@
+# License .to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+# pylint: disable=invalid-name
+"""
+The Relay Virtual Machine serializer.
+
+Python interface for serializing a Relay VM.
+"""
+import tvm
+from . import _vm
+from . import vm as rly_vm
+
+def _create_serializer(vm):
+    """Create a VM serializer.
+
+    Parameters
+    ----------
+    vm : Union[VirtualMachine, :py:class:`~tvm.module.Module`]
+        The virtual machine to be serialized.
+
+    Returns
+    -------
+    ret : Serializer
+        The created virtual machine serializer.
+    """
+    if isinstance(vm, rly_vm.VirtualMachine):
+        vm = vm.module
+    elif not isinstance(vm, tvm.module.Module):
+        raise TypeError("vm is expected to be the type of VirtualMachine or " +
+                        "tvm.Module, but received {}".format(type(vm)))
+
+    return _vm._Serializer(vm)
+
+
+class Serializer:
+    """Relay VM serializer."""
+    def __init__(self, vm):
+        self.mod = _create_serializer(vm)
+        self._get_lib = self.mod["get_lib"]
+        self._get_bytecode = self.mod["get_bytecode"]
+        self._get_globals = self.mod["get_globals"]
+        self._get_stats = self.mod["get_stats"]
+        self._get_primitive_ops = self.mod["get_primitive_ops"]
+        self._serialize = self.mod["serialize"]
+
+    @property
+    def stats(self):
+        """Get the statistics of the Relay VM.
+
+        Returns
+        -------
+        ret : String
+            The serialized statistic information.
+        """
+        return self._get_stats()
+
+    @property
+    def primitive_ops(self):
+        """Get the name of the primitive ops that are executed in the VM.
+
+        Returns
+        -------
+        ret : List[:py:class:`~tvm.expr.StringImm`]
+            The list of primitive ops.
+        """
+        return [prim_op.value for prim_op in self._get_primitive_ops()]
+
+    @property
+    def bytecode(self):
+        """Get the bytecode of the Relay VM.
+
+        Returns
+        -------
+        ret : String
+            The serialized bytecode.
+
+        Notes
+        -----
+        The bytecode is in the following format:
+          func_name reg_file_size num_instructions
+          param1 param2 ... paramM
+          instruction1
+          instruction2
+          ...
+          instructionN
+
+        Each instruction is printed in the following format:
+          hash opcode field1 ... fieldX # The text format.
+
+        The part starting from # is only used for visualization and debugging.
+        The real serialized code doesn't contain it, therefore the deserializer
+        doesn't need to deal with it as well.
+        """
+        return self._get_bytecode()
+
+    @property
+    def globals(self):
+        """Get the globals used by the Relay VM.
+
+        Returns
+        -------
+        ret : List[:py:class:`~tvm.expr.StringImm`]
+            The serialized globals.
+        """
+        return [glb.value for glb in self._get_globals()]
+
+    def serialize(self):
+        """Serialize the Relay VM.
+
+        Returns
+        -------
+        code : bytearray
+            The binary blob representing a serialized Relay VM. It can then be
+            saved to disk and later deserialized into a new VM.
+
+        lib : :py:class:`~tvm.module.Module`
+            The runtime module that contains the generated code. It is
+            basically a library that is composed of hardware dependent code.
+
+        Notes
+        -----
+        The returned code is organized with the following sections in order.
+         - Global section. This section contains the globals used by the
+         virtual machine.
+         - Constant section. This section is used to store the constant pool of
+         a virtual machine.
+         - Primitive name section. This section is introduced to accommodate
+         the list of primitive operator names that will be invoked by the
+         virtual machine.
+         - Code section. The VM functions, including bytecode, are sitting in
+         this section.
+
+        Examples
+        --------
+        .. code-block:: python
+
+            import numpy as np
+            import tvm
+            from tvm import relay
+
+            # define a simple network.
+            x = relay.var('x', shape=(10, 10))
+            f = relay.Function([x], x + x)
+            mod = relay.Module({"main": f})
+
+            # create a Relay VM.
+            ctx = tvm.cpu()
+            target = "llvm"
+            compiler = relay.vm.VMCompiler()
+            vm = compiler.compile(mod, target)
+            vm.init(ctx)
+
+            # serialize.
+            ser = relay.serializer.Serializer(vm)
+            code, lib = ser.serialize()
+
+            # save and load the code and lib file.
+            tmp = tvm.contrib.util.tempdir()
+            path_lib = tmp.relpath("lib.so")
+            lib.export_library(path_lib)
+            with open(tmp.relpath("code.bc"), "wb") as fo:
+                fo.write(code)
+
+            loaded_lib = tvm.module.load(path_lib)
+            loaded_code = bytearray(open(tmp.relpath("code.bc"), "rb").read())
+
+            # deserialize.
+            deser = relay.deserializer.Deserializer(loaded_code, loaded_lib)
+            des_vm = deser.deserialize()
+
+            # execute the deserialized vm.
+            des_vm.init(ctx)
+            x_data = np.random.rand(10, 10).astype('float32')
+            res = des_vm.run(x_data)
+            print(res.asnumpy())
+        """
+        return self._serialize(), self._get_lib()
diff --git a/python/tvm/relay/backend/vm.py b/python/tvm/relay/backend/vm.py
index 5f3413ae82c2..752e9b2cb10b 100644
--- a/python/tvm/relay/backend/vm.py
+++ b/python/tvm/relay/backend/vm.py
@@ -16,13 +16,14 @@
 # under the License.
 # pylint: disable=no-else-return, unidiomatic-typecheck, undefined-variable, invalid-name
 """
-The Relay Virtual Vachine.
+The Relay Virtual Machine.
 
 Implements a Python interface to compiling and executing on the Relay VM.
 """
 import numpy as np
 
 import tvm
+from tvm._ffi.runtime_ctypes import TVMByteArray
 from . import _vm
 from . import vmobj as _obj
 from .interpreter import Executor
@@ -71,6 +72,7 @@ class VirtualMachine(object):
     def __init__(self, mod):
         self.mod = mod
         self._init = self.mod["init"]
+        self._load_params = self.mod["load_params"]
         self._invoke = self.mod["invoke"]
 
     def init(self, ctx):
@@ -84,6 +86,23 @@ def init(self, ctx):
         args = [ctx.device_type, ctx.device_id]
         self._init(*args)
 
+    def load_params(self, params):
+        """Load parameters for the VM.
+
+        Parameters
+        ----------
+        params : Union[bytearray, Dict]
+            The dictionary that contains serialized parameters.
+        """
+        if isinstance(params, dict):
+            params = tvm.relay.save_param_dict(params)
+        elif isinstance(params, (bytes, str)):
+            params = bytearray(params)
+        if not isinstance(params, (bytearray, TVMByteArray)):
+            raise TypeError("params must be a bytearray")
+
+        self._load_params(bytearray(params))
+
     def invoke(self, func_name, *args):
         """Invoke a function.
 
@@ -118,6 +137,11 @@ def run(self, *args):
         """
         return self.invoke("main", *args)
 
+    @property
+    def module(self):
+        """Return the runtime module contained in a virtual machine."""
+        return self.mod
+
 
 class VMCompiler(object):
     """Build Relay module to run on VM runtime."""
diff --git a/src/relay/backend/vm/compiler.cc b/src/relay/backend/vm/compiler.cc
index 11a3d0403067..853cd30f82c3 100644
--- a/src/relay/backend/vm/compiler.cc
+++ b/src/relay/backend/vm/compiler.cc
@@ -745,7 +745,7 @@ class VMCompiler : public runtime::ModuleNode {
     }
 #endif  // USE_RELAY_DEBUG
 
-    PopulatePackedFuncMap();
+    LibraryCodegen();
 
     for (auto gv : context_.global_map) {
       vm_->global_map.insert({gv.first->name_hint, gv.second});
@@ -775,26 +775,28 @@ class VMCompiler : public runtime::ModuleNode {
     }
   }
 
-  void PopulatePackedFuncMap() {
+  void LibraryCodegen() {
     auto const& lowered_funcs = context_.lowered_funcs;
     if (lowered_funcs.size() == 0) {
       return;
     }
-    runtime::Module mod;
     // TODO(@icemelon9): support heterogeneous targets
     Target target;
     for (auto kv : targets_) {
       target = kv.second;
     }
     if (const auto* f = runtime::Registry::Get("relay.backend.build")) {
-      mod = (*f)(tvm::Array<LoweredFunc>(lowered_funcs.begin(), lowered_funcs.end()),
-              target, target_host_);
+      runtime::Module mod =
+          (*f)(tvm::Array<LoweredFunc>(lowered_funcs.begin(), lowered_funcs.end()), target,
+               target_host_);
+      CHECK(mod.operator->());
+      vm_->lib = mod;
     } else {
       LOG(FATAL) << "relay.backend.build is not registered";
     }
-    CHECK(mod.operator->());
+    size_t primitive_index = 0;
     for (auto lfunc : lowered_funcs) {
-      vm_->packed_funcs.push_back(mod.GetFunction(lfunc->name));
+      vm_->primitive_map.insert({lfunc->name, primitive_index++});
     }
   }
 
diff --git a/src/relay/backend/vm/deserializer.cc b/src/relay/backend/vm/deserializer.cc
new file mode 100644
index 000000000000..6cf76081de13
--- /dev/null
+++ b/src/relay/backend/vm/deserializer.cc
@@ -0,0 +1,324 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file src/relay/backend/vm/deserializer.cc
+ * \brief Implementation of APIs to deserialize the serialized VM bytecode.
+ */
+
+#include "deserializer.h"
+
+#include <tvm/runtime/registry.h>
+#include <memory>
+#include <sstream>
+
+#include "serialize_util.h"
+
+namespace tvm {
+namespace relay {
+namespace vm {
+
+#define STREAM_CHECK(val, section)                                         \
+  CHECK(val) << "Invalid VM file format in the " << section << " section." \
+             << "\n";
+
+void Deserializer::Init(const std::string& code, const runtime::Module& lib) {
+  code_ = code;
+  vm_ = std::make_shared<VirtualMachine>();
+  vm_->lib = lib;
+  strm_ = new dmlc::MemoryStringStream(&code_);
+}
+
+runtime::PackedFunc Deserializer::GetFunction(
+    const std::string& name,
+    const std::shared_ptr<ModuleNode>& sptr_to_self) {
+  if (name == "deserialize") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      this->Deserialize();
+      *rv = runtime::Module(vm_);
+    });
+  } else {
+    LOG(FATAL) << "Unknown packed function: " << name;
+    return PackedFunc([sptr_to_self, name](TVMArgs args, TVMRetValue* rv) {});
+  }
+}
+
+void Deserializer::Deserialize() {
+  // Check header.
+  uint64_t header;
+  STREAM_CHECK(strm_->Read(&header), "header");
+  STREAM_CHECK(header == kTVMVMBytecodeMagic, "header");
+
+  // Check version.
+  std::string version;
+  STREAM_CHECK(strm_->Read(&version), "version");
+  STREAM_CHECK(version == TVM_VERSION, "version");
+
+  // Global section.
+  DeserializeGlobalSection();
+
+  // Constant section.
+  DeserializeConstantSection();
+
+  // Primitive names that will be invoked by `InvokePacked` instructions.
+  DeserializePrimitiveOpNames();
+
+  // Code section.
+  DeserializeCodeSection();
+}
+
+void Deserializer::DeserializeGlobalSection() {
+  std::vector<std::string> globals;
+  STREAM_CHECK(strm_->Read(&globals), "global");
+  for (size_t i = 0; i < globals.size(); i++) {
+    vm_->global_map.insert({globals[i], i});
+  }
+}
+
+void Deserializer::DeserializeConstantSection() {
+  uint64_t sz;
+  // Load the number of constants.
+  STREAM_CHECK(strm_->Read(&sz, sizeof(sz)), "constant");
+
+  size_t size = static_cast<size_t>(sz);
+  // Load each of the constants.
+  for (size_t i = 0; i < size; i++) {
+    runtime::NDArray constant;
+    STREAM_CHECK(constant.Load(strm_), "constant");
+    runtime::Object obj = runtime::Object::Tensor(constant);
+    vm_->constants.push_back(obj);
+  }
+}
+
+void Deserializer::DeserializePrimitiveOpNames() {
+  std::vector<std::string> primitive_names;
+  STREAM_CHECK(strm_->Read(&primitive_names), "primitive name");
+  for (size_t i = 0; i < primitive_names.size(); i++) {
+    vm_->primitive_map.insert({primitive_names[i], i});
+  }
+}
+
+// Extract the `cnt` number of fields started at `start` from the list
+// `instr_fields`.
+inline std::vector<Index> ExtractFields(const std::vector<Index>& instr_fields,
+                                        Index start,
+                                        Index cnt) {
+  CHECK_LE(static_cast<size_t>(start + cnt), instr_fields.size());
+  std::vector<Index> ret;
+  for (auto i = start; i < start + cnt; i++) {
+    ret.push_back(instr_fields[i]);
+  }
+  return ret;
+}
+
+Instruction DeserializeInstruction(const VMInstructionSerializer& instr) {
+  Opcode opcode = static_cast<Opcode>(instr.opcode);
+  switch (opcode) {
+    case Opcode::Move: {
+      // Number of fields = 2
+      DCHECK_EQ(instr.fields.size(), 2U);
+      return Instruction::Move(instr.fields[0], instr.fields[1]);
+    }
+    case Opcode::Ret: {
+      // Number of fields = 1
+      DCHECK_EQ(instr.fields.size(), 1U);
+      return Instruction::Ret(instr.fields[0]);
+    }
+    case Opcode::Fatal: {
+      // Number of fields = 0
+      DCHECK(instr.fields.empty());
+      return Instruction::Fatal();
+    }
+    case Opcode::InvokePacked: {
+      // Number of fields = 3 + instr.arity
+      DCHECK_GE(instr.fields.size(), 3U);
+      DCHECK_EQ(instr.fields.size(), 3U + static_cast<size_t>(instr.fields[1]));
+
+      Index packed_index = instr.fields[0];
+      Index arity = instr.fields[1];
+      Index output_size = instr.fields[2];
+      std::vector<RegName> args = ExtractFields(instr.fields, 3, arity);
+      return Instruction::InvokePacked(packed_index, arity, output_size, args);
+    }
+    case Opcode::AllocTensor: {
+      // Number of fields = 5 + instr.alloc_tensor.ndim
+      DCHECK_GE(instr.fields.size(), 5U);
+      DCHECK_EQ(instr.fields.size(), 5U + static_cast<size_t>(instr.fields[3]));
+
+      DLDataType dtype;
+      dtype.code = instr.fields[0];
+      dtype.bits = instr.fields[1];
+      dtype.lanes = instr.fields[2];
+
+      Index ndim = instr.fields[3];
+      RegName dst = instr.fields[4];
+
+      std::vector<Index> shape = ExtractFields(instr.fields, 5, ndim);
+
+      return Instruction::AllocTensor(shape, dtype, dst);
+    }
+    case Opcode::AllocTensorReg: {
+      // Number of fields = 5
+      DCHECK_EQ(instr.fields.size(), 5U);
+      Index shape_register = instr.fields[0];
+
+      DLDataType dtype;
+      dtype.code = instr.fields[1];
+      dtype.bits = instr.fields[2];
+      dtype.lanes = instr.fields[3];
+
+      RegName dst = instr.fields[4];
+
+      return Instruction::AllocTensorReg(shape_register, dtype, dst);
+    }
+    case Opcode::AllocDatatype: {
+      // Number of fields = 3 + instr.num_fields
+      DCHECK_GE(instr.fields.size(), 3U);
+      DCHECK_EQ(instr.fields.size(), 3U + static_cast<size_t>(instr.fields[1]));
+
+      Index constructor_tag = instr.fields[0];
+      Index num_fields = instr.fields[1];
+      RegName dst = instr.fields[2];
+      std::vector<Index> fields = ExtractFields(instr.fields, 3, num_fields);
+
+      return Instruction::AllocDatatype(constructor_tag, num_fields, fields, dst);
+    }
+    case Opcode::AllocClosure: {
+      // Number of fields = 3 + instr.num_freevar
+      DCHECK_GE(instr.fields.size(), 3U);
+      DCHECK_EQ(instr.fields.size(), 3U + static_cast<size_t>(instr.fields[1]));
+
+      Index clo_index = instr.fields[0];
+      Index num_freevar = instr.fields[1];
+      RegName dst = instr.fields[2];
+      std::vector<Index> free_vars = ExtractFields(instr.fields, 3, num_freevar);
+
+      return Instruction::AllocClosure(clo_index, num_freevar, free_vars, dst);
+    }
+    case Opcode::If: {
+      // Number of fields = 4
+      DCHECK_EQ(instr.fields.size(), 4U);
+      Index test = instr.fields[0];
+      Index target = instr.fields[1];
+      Index true_offset = instr.fields[2];
+      Index false_offset = instr.fields[3];
+
+      return Instruction::If(test, target, true_offset, false_offset);
+    }
+    case Opcode::Invoke: {
+      // Number of fields = 3 + instr.num_args
+      DCHECK_GE(instr.fields.size(), 3U);
+      DCHECK_EQ(instr.fields.size(), 3U + static_cast<size_t>(instr.fields[1]));
+
+      Index func_index = instr.fields[0];
+      Index num_args = instr.fields[1];
+      RegName dst = instr.fields[2];
+      std::vector<Index> args = ExtractFields(instr.fields, 3, num_args);
+
+      return Instruction::Invoke(func_index, args, dst);
+    }
+    case Opcode::InvokeClosure: {
+      // Number of fields = 3 + instr.num_closure_args
+      DCHECK_GE(instr.fields.size(), 3U);
+      DCHECK_EQ(instr.fields.size(), 3U + static_cast<size_t>(instr.fields[1]));
+
+      Index closure = instr.fields[0];
+      Index num_closure_args = instr.fields[1];
+      RegName dst = instr.fields[2];
+      std::vector<Index> args = ExtractFields(instr.fields, 3, num_closure_args);
+
+      return Instruction::InvokeClosure(closure, args, dst);
+    }
+    case Opcode::LoadConst: {
+      // Number of fields = 2
+      DCHECK_EQ(instr.fields.size(), 2U);
+      return Instruction::LoadConst(instr.fields[0], instr.fields[1]);
+    }
+    case Opcode::LoadConsti: {
+      // Number of fields = 2
+      DCHECK_EQ(instr.fields.size(), 2U);
+      return Instruction::LoadConsti(instr.fields[0], instr.fields[1]);
+    }
+    case Opcode::GetField: {
+      // Number of fields = 3
+      DCHECK_EQ(instr.fields.size(), 3U);
+      return Instruction::GetField(instr.fields[0], instr.fields[1], instr.fields[2]);
+    }
+    case Opcode::GetTag: {
+      // Number of fields = 2
+      DCHECK_EQ(instr.fields.size(), 2U);
+      return Instruction::GetTag(instr.fields[0], instr.fields[1]);
+    }
+    case Opcode::Goto: {
+      // Number of fields = 1
+      DCHECK_EQ(instr.fields.size(), 1U);
+      return Instruction::Goto(instr.fields[0]);
+    }
+    default:
+      LOG(FATAL) << "Invalid opcode" << instr.opcode;
+      return Instruction();
+  }
+}
+
+void Deserializer::DeserializeCodeSection() {
+  // Load the number of functions.
+  uint64_t sz;
+  STREAM_CHECK(strm_->Read(&sz, sizeof(sz)), "code");
+
+  size_t num_funcs = static_cast<size_t>(sz);
+  vm_->functions.resize(num_funcs);
+  for (size_t i = 0; i < num_funcs; i++) {
+    // Load the function info.
+    VMFunctionSerializer loaded_func;
+    STREAM_CHECK(loaded_func.Load(strm_), "code/function");
+
+    // Load the instructions.
+    std::vector<Instruction> instructions;
+    for (size_t j = 0; j < loaded_func.num_instructions; j++) {
+      VMInstructionSerializer instr;
+      std::vector<Index> instr_fields;
+      STREAM_CHECK(instr.Load(strm_), "code/instruction");
+      instructions.push_back(DeserializeInstruction(instr));
+    }
+
+    // Create the VM function.
+    VMFunction vm_func = VMFunction(loaded_func.name,
+                                    loaded_func.params,
+                                    instructions,
+                                    loaded_func.register_file_size);
+    auto it = vm_->global_map.find(loaded_func.name);
+    CHECK(it != vm_->global_map.end());
+    CHECK_LE(it->second, vm_->global_map.size());
+    vm_->functions[it->second] = vm_func;
+  }
+}
+
+runtime::Module CreateDeserializer(const std::string& code, const runtime::Module lib) {
+  std::shared_ptr<Deserializer> exec = std::make_shared<Deserializer>();
+  exec->Init(code, lib);
+  return runtime::Module(exec);
+}
+
+TVM_REGISTER_GLOBAL("relay._vm._Deserializer")
+.set_body_typed(CreateDeserializer);
+
+}  // namespace vm
+}  // namespace relay
+}  // namespace tvm
diff --git a/src/relay/backend/vm/deserializer.h b/src/relay/backend/vm/deserializer.h
new file mode 100644
index 000000000000..0caf72bee92c
--- /dev/null
+++ b/src/relay/backend/vm/deserializer.h
@@ -0,0 +1,102 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file src/relay/backend/vm/deserializer.h
+ * \brief Define a deserializer for the serialized Relay VM.
+ */
+
+#ifndef TVM_RELAY_BACKEND_VM_DESERIALIZER_H_
+#define TVM_RELAY_BACKEND_VM_DESERIALIZER_H_
+
+#include <dmlc/memory_io.h>
+#include <tvm/packed_func_ext.h>
+#include <tvm/runtime/packed_func.h>
+#include <tvm/runtime/vm.h>
+
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+namespace tvm {
+namespace relay {
+namespace vm {
+
+using namespace tvm::runtime::vm;
+namespace runtime = tvm::runtime;
+
+class Deserializer : public runtime::ModuleNode {
+ public:
+  /*!
+   * \brief Initialize the deserializer for creating a virtual machine object.
+   *
+   * \param code The serialized code.
+   * \param lib The serialized runtime module/library that contains the
+   * hardware dependent code.
+   */
+  inline void Init(const std::string& code, const runtime::Module& lib);
+
+  /*!
+   * \brief Return the member function to the frontend.
+   *
+   * \param name The name of the function.
+   * \param sptr_to_self The pointer to the module node.
+   *
+   * \return The corresponding member function.
+   */
+  PackedFunc GetFunction(const std::string& name,
+                         const std::shared_ptr<ModuleNode>& sptr_to_self) final;
+
+  const char* type_key() const final { return "Deserializer"; }
+
+  /*! \brief Deserialize the serialized VM. */
+  void Deserialize();
+
+  virtual ~Deserializer() { delete strm_; }
+
+ private:
+  /*! \brief Deserialize the globals in `vm_`. */
+  void DeserializeGlobalSection();
+
+  /*! \brief Deserialize the constant pool in `vm_`. */
+  void DeserializeConstantSection();
+
+  /*! \brief Deserialize primitive op names in `vm_`. */
+  void DeserializePrimitiveOpNames();
+
+  /*! \brief Deserialize the vm functions in `vm_`. */
+  void DeserializeCodeSection();
+
+  /*! \brief The code to be serialized. */
+  std::string code_;
+
+  /*! \brief The stream used for serialization. */
+  dmlc::Stream* strm_;
+
+  /*! \brief The VM to be created. */
+  std::shared_ptr<VirtualMachine> vm_;
+};
+
+}  // namespace vm
+}  // namespace relay
+}  // namespace tvm
+
+#endif  // TVM_RELAY_BACKEND_VM_DESERIALIZER_H_
diff --git a/src/relay/backend/vm/serialize_util.h b/src/relay/backend/vm/serialize_util.h
new file mode 100644
index 000000000000..3e7508ebee9b
--- /dev/null
+++ b/src/relay/backend/vm/serialize_util.h
@@ -0,0 +1,164 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file src/relay/backend/vm/serialize_util.h
+ * \brief Definitions of helpers for serializing and deserializing a Relay VM.
+ */
+#ifndef TVM_RELAY_BACKEND_VM_SERIALIZE_UTIL_H_
+#define TVM_RELAY_BACKEND_VM_SERIALIZE_UTIL_H_
+
+#include <dmlc/common.h>
+#include <dmlc/memory_io.h>
+#include <tvm/runtime/vm.h>
+
+#include <functional>
+#include <string>
+#include <vector>
+
+namespace tvm {
+namespace relay {
+namespace vm {
+
+/*! \brief The magic number for the serialized VM bytecode file  */
+constexpr uint64_t kTVMVMBytecodeMagic = 0xD225DE2F4214151D;
+
+template <typename T>
+static inline size_t VectorHash(size_t key, const std::vector<T>& values) {
+  for (const auto& it : values) {
+    key = dmlc::HashCombine(key, it);
+  }
+  return key;
+}
+
+// A struct to hold the funciton info in the code section.
+struct VMFunctionSerializer {
+  /*! \brief The name of the VMFunction. */
+  std::string name;
+  /*! \brief The number of registers used by the VMFunction. */
+  Index register_file_size;
+  /*! \brief The number of instructions in the VMFunction. */
+  size_t num_instructions;
+  /*! \brief The parameters of the VMFunction. */
+  std::vector<std::string> params;
+
+  VMFunctionSerializer() = default;
+
+  VMFunctionSerializer(const std::string& name,
+                       Index register_file_size,
+                       size_t num_instructions,
+                       const std::vector<std::string>& params)
+      : name(name),
+        register_file_size(register_file_size),
+        num_instructions(num_instructions),
+        params(params) {}
+
+  /*!
+   * \brief Load the serialized function header.
+   * \param strm The stream used to load data.
+   * \return True if successful. Otherwise, false.
+   */
+  bool Load(dmlc::Stream* strm) {
+    std::vector<std::string> func_info;
+    if (!strm->Read(&func_info)) return false;
+    CHECK_EQ(func_info.size(), 3U) << "Failed to decode the vm function."
+                                   << "\n";
+    name = func_info[0];
+    register_file_size = std::stoll(func_info[1]);
+    // Get the number of instructions.
+    num_instructions = static_cast<size_t>(std::stoll(func_info[2]));
+    return strm->Read(&params);
+  }
+
+  /*!
+   * \brief Save the VM function header into the serialized form. 
+   * \param strm The stream used to save data.
+   */
+  void Save(dmlc::Stream* strm) const {
+    std::vector<std::string> func_info;
+    func_info.push_back(name);
+    func_info.push_back(std::to_string(register_file_size));
+    func_info.push_back(std::to_string(num_instructions));
+    strm->Write(func_info);
+    strm->Write(params);
+  }
+};
+
+struct VMInstructionSerializer {
+  /*! \brief The opcode of the instruction. */
+  Index opcode;
+  /*! \brief The fields of the instruction. */
+  std::vector<Index> fields;
+
+  VMInstructionSerializer() = default;
+
+  VMInstructionSerializer(Index opcode, const std::vector<Index>& fields) :
+    opcode(opcode), fields(fields) {}
+
+  /*!
+   * \brief Compute the hash of the serialized instruction. 
+   * \return The hash that combines the opcode and all fields of the VM
+   * instruction.
+   */
+  Index Hash() const {
+    size_t key = static_cast<size_t>(opcode);
+    key = VectorHash(key, fields);
+    return key;
+  }
+
+  /*!
+   * \brief Load the serialized instruction.
+   * \param strm The stream used to load data.
+   * \return True if successful. Otherwise, false.
+   */
+  bool Load(dmlc::Stream* strm) {
+    std::vector<Index> instr;
+    if (!strm->Read(&instr)) return false;
+    CHECK_GE(instr.size(), 2U);
+    Index loaded_hash = instr[0];
+    opcode = instr[1];
+
+    for (size_t i = 2; i < instr.size(); i++) {
+      fields.push_back(instr[i]);
+    }
+
+    Index hash = Hash();
+    CHECK_EQ(loaded_hash, hash) << "Found mismatch in hash for opcode: "
+                                << opcode << "\n";
+    return true;
+  }
+
+  /*!
+   * \brief Save the instruction into the serialized form. 
+   * \param strm The stream used to save data.
+   */
+  void Save(dmlc::Stream* strm) const {
+    Index hash = Hash();
+    std::vector<Index> serialized({hash, opcode});
+    serialized.insert(serialized.end(), fields.begin(), fields.end());
+    strm->Write(serialized);
+  }
+};
+
+}  // namespace vm
+}  // namespace relay
+}  // namespace tvm
+
+#endif  // TVM_RELAY_BACKEND_VM_SERIALIZE_UTIL_H_
diff --git a/src/relay/backend/vm/serializer.cc b/src/relay/backend/vm/serializer.cc
new file mode 100644
index 000000000000..d6e44b4af1f8
--- /dev/null
+++ b/src/relay/backend/vm/serializer.cc
@@ -0,0 +1,438 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file src/relay/backend/vm/serializer.cc
+ * \brief Implementation of serializing APIs for the Relay VM.
+ */
+#include "serializer.h"
+
+#include <tvm/runtime/registry.h>
+#include <tvm/runtime/c_runtime_api.h>
+
+#include <algorithm>
+#include <memory>
+#include <sstream>
+#include <utility>
+#include <vector>
+
+#include "serialize_util.h"
+
+namespace tvm {
+namespace relay {
+namespace vm {
+
+void Serializer::Init(const VirtualMachine* vm) {
+  vm_ = vm;
+  // Initialize the stream object.
+  strm_ = new dmlc::MemoryStringStream(&code_);
+}
+
+runtime::PackedFunc Serializer::GetFunction(
+    const std::string& name,
+    const std::shared_ptr<ModuleNode>& sptr_to_self) {
+  if (name == "get_lib") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->GetLib();
+    });
+  } else if (name == "get_primitive_ops") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->GetPrimitiveOps();
+    });
+  } else if (name == "get_bytecode") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->GetBytecode();
+    });
+  } else if (name == "get_globals") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->GetGlobals();
+    });
+  } else if (name == "get_stats") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->Stats();
+    });
+  } else if (name == "serialize") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      *rv = this->Serialize();
+    });
+  } else {
+    LOG(FATAL) << "Unknown packed function: " << name;
+    return PackedFunc([sptr_to_self, name](TVMArgs args, TVMRetValue* rv) {});
+  }
+}
+
+tvm::Array<tvm::Expr> Serializer::GetPrimitiveOps() const {
+  std::vector<tvm::Expr> ret;
+  for (const auto& it : vm_->primitive_map) {
+    auto packed_name = tvm::ir::StringImm::make(it.first);
+    auto packed_index = static_cast<size_t>(it.second);
+    if (ret.size() <= packed_index) {
+      ret.resize(packed_index + 1);
+    }
+    ret[packed_index] = packed_name;
+  }
+  return ret;
+}
+
+std::string Serializer::Stats() const {
+  std::ostringstream oss;
+  oss << "Relay VM statistics:" << std::endl;
+
+  // Get the number of constants and the shape of each of them.
+  oss << "  Constant shapes (# " << vm_->constants.size() << "): [";
+  for (const auto& it : vm_->constants) {
+    auto cell = it.AsTensor();
+    CHECK(cell.operator->());
+    runtime::NDArray data = cell->data;
+    const auto& shape = data.Shape();
+
+    // Scalar
+    if (shape.empty()) {
+      oss << "scalar, ";
+      continue;
+    }
+
+    oss << "[";
+    for (auto s : shape) {
+      oss << s << ", ";
+    }
+    oss.seekp(-2, oss.cur);
+    oss << "], " << std::endl;
+  }
+  if (!vm_->constants.empty()) oss.seekp(-2, oss.cur);
+  oss << "]" << std::endl;
+
+  // Get the number of globals and the name of each of them.
+  oss << "  Globals (#" << vm_->global_map.size() << "): [";
+  for (const auto& it : vm_->global_map) {
+    oss << "(\"" << it.first << "\", " << it.second << ")" << ", ";
+  }
+  if (!vm_->global_map.empty()) oss.seekp(-2, oss.cur);
+  oss << "]" << std::endl;
+
+  // Get the number of primitive ops and the name of each of them.
+  oss << "  Primitive ops (#" << vm_->primitive_map.size() << "): [";
+  const auto& prim_ops = GetPrimitiveOps();
+  for (const auto& it : prim_ops) {
+    oss << it << ", ";
+  }
+  if (!prim_ops.empty()) oss.seekp(-2, oss.cur);
+  oss << "]" << std::endl;
+
+  return oss.str();
+}
+
+TVMByteArray Serializer::Serialize() {
+  uint64_t header = kTVMVMBytecodeMagic;
+  strm_->Write(header);
+  std::string version = TVM_VERSION;
+  strm_->Write(version);
+
+  // Global section.
+  SerializeGlobalSection();
+
+  // Constant section.
+  SerializeConstantSection();
+
+  // Primitive names.
+  SerializePrimitiveOpNames();
+
+  // Code section.
+  SerializeCodeSection();
+
+  TVMByteArray arr;
+  arr.data = code_.c_str();
+  arr.size = code_.length();
+  return arr;
+}
+
+void Serializer::SerializeGlobalSection() {
+  auto globals = GetGlobals();
+  std::vector<std::string> glbs;
+  for (const auto& it : globals) {
+    glbs.push_back(it.as<tvm::ir::StringImm>()->value);
+  }
+  strm_->Write(glbs);
+}
+
+void Serializer::SerializeConstantSection() {
+  std::vector<DLTensor*> arrays;
+  for (const auto& obj : vm_->constants) {
+    auto cell = obj.AsTensor();
+    runtime::NDArray data = cell->data;
+    arrays.push_back(const_cast<DLTensor*>(data.operator->()));
+  }
+  strm_->Write(static_cast<uint64_t>(vm_->constants.size()));
+  for (const auto& it : arrays) {
+    runtime::SaveDLTensor(strm_, it);
+  }
+}
+
+void Serializer::SerializePrimitiveOpNames() {
+  auto names = GetPrimitiveOps();
+  std::vector<std::string> primitive_names;
+  for (const auto& it : names) {
+    primitive_names.push_back(it.as<tvm::ir::StringImm>()->value);
+  }
+  strm_->Write(primitive_names);
+}
+
+// Serialize a virtual machine instruction. It creates a list that contains the
+// hash, opcode, and all fields of an instruction.
+//
+// For example, the function signature used to create an `AllocTensor`
+// instruction is:
+//   Instruction AllocTensor(std::vector<Index> shape, DLDataType dtype, RegName dst)
+//
+// The serialized form will be:
+//   `hash 5 dtype.code dtype.bits dtype.lanes ndim dst_register val1 val2 ... valn`
+//
+// where hash is the hash of serialized instruction that is computed internally
+// by the `VMInstructionSerializer`. It is used for sanity check before decoding.
+// 5 shows opcode of `AllocTensor`, `(dtype.code dtype.bits dtype.lanes)`
+// represents a `DLDataType`, `ndim` is the number of dimensions, `dst_register`
+// is the destination register, and the rest of it together indicates the shape
+// of the tensor to be allocated.
+VMInstructionSerializer SerializeInstruction(const Instruction& instr) {
+  std::vector<Index> fields;
+  // Save the opcode.
+  DLOG(INFO) << "Serializing: " << instr << std::endl;
+  switch (instr.op) {
+    case Opcode::Move: {
+      // Number of fields = 2
+      fields.assign({instr.from, instr.dst});
+      break;
+    }
+    case Opcode::Ret: {
+      // Number of fields = 1
+      fields.push_back(instr.result);
+      break;
+    }
+    case Opcode::Fatal: {
+      // Number of fields = 0
+      break;
+    }
+    case Opcode::InvokePacked: {
+      // Number of fields = 3 + instr.arity
+      // Note that arity includes both input arguments and outputs. We will
+      // put all the `arity` number of fields in the end for serialization.
+      fields.assign({instr.packed_index, instr.arity, instr.output_size});
+      // Save the args.
+      fields.insert(fields.end(), instr.packed_args, instr.packed_args + instr.arity);
+      break;
+    }
+    case Opcode::AllocTensor: {
+      // Number of fields = 5 + instr.alloc_tensor.ndim
+      // Save `DLDataType` and the dst register.
+      const auto& dtype = instr.alloc_tensor.dtype;
+      fields.assign({dtype.code, dtype.bits, dtype.lanes});
+
+      // The number of dimensions is not needed for constructing an
+      // `AllocTensor` instruction as it equals to the length of the `shape`
+      // vector. However, we save it to conveniently deserialize the instruction
+      // because we will know how many fields are needed by the `shape` argument.
+      fields.push_back(instr.alloc_tensor.ndim);
+      fields.push_back(instr.dst);
+
+      // Save the shape of the tensor.
+      // Note that this field is rotated to the end of the list.
+      fields.insert(fields.end(), instr.alloc_tensor.shape,
+                    instr.alloc_tensor.shape + instr.alloc_tensor.ndim);
+      break;
+    }
+    case Opcode::AllocTensorReg: {
+      // Number of fields = 5
+      fields.push_back(instr.alloc_tensor_reg.shape_register);
+      // Save `DLDataType` and the dst register.
+      const auto& dtype = instr.alloc_tensor.dtype;
+      fields.assign({dtype.code, dtype.bits, dtype.lanes});
+      fields.push_back(instr.dst);
+      break;
+    }
+    case Opcode::AllocDatatype: {
+      // Number of fields = 3 + instr.num_fields
+      fields.assign({instr.constructor_tag, instr.num_fields, instr.dst});
+
+      // Save the fields.
+      fields.insert(fields.end(), instr.datatype_fields,
+                    instr.datatype_fields + instr.num_fields);
+      break;
+    }
+    case Opcode::AllocClosure: {
+      // Number of fields = 3 + instr.num_freevar
+      fields.assign({instr.clo_index, instr.num_freevar, instr.dst});
+
+      // Save the free vars.
+      fields.insert(fields.end(), instr.free_vars,
+                    instr.free_vars + instr.num_freevar);
+      break;
+    }
+    case Opcode::If: {
+      // Number of fields = 4
+      fields.assign({instr.if_op.test,
+                     instr.if_op.target,
+                     instr.if_op.true_offset,
+                     instr.if_op.false_offset});
+      break;
+    }
+    case Opcode::Invoke: {
+      // Number of fields = 3 + instr.num_args
+      fields.assign({instr.func_index, instr.num_args, instr.dst});
+
+      // Save the args.
+      fields.insert(fields.end(), instr.invoke_args_registers,
+                    instr.invoke_args_registers + instr.num_args);
+      break;
+    }
+    case Opcode::InvokeClosure: {
+      // Number of fields = 3 + instr.num_closure_args
+      fields.assign({instr.closure, instr.num_closure_args, instr.dst});
+
+      // Save the args.
+      fields.insert(fields.end(), instr.closure_args,
+                    instr.closure_args + instr.num_closure_args);
+      break;
+    }
+    case Opcode::LoadConst: {
+      // Number of fields = 2
+      fields.assign({instr.const_index, instr.dst});
+      break;
+    }
+    case Opcode::LoadConsti: {
+      // Number of fields = 2
+      fields.assign({instr.load_consti.val, instr.dst});
+      break;
+    }
+    case Opcode::GetField: {
+      // Number of fields = 3
+      fields.assign({instr.object, instr.field_index, instr.dst});
+      break;
+    }
+    case Opcode::GetTag: {
+      // Number of fields = 2
+      fields.assign({instr.get_tag.object, instr.dst});
+      break;
+    }
+    case Opcode::Goto: {
+      // Number of fields = 1
+      fields.push_back(instr.pc_offset);
+      break;
+    }
+    default:
+      LOG(FATAL) << "Invalid opcode" << static_cast<int>(instr.op);
+      break;
+  }
+
+  return VMInstructionSerializer(static_cast<Index>(instr.op), fields);
+}
+
+void Serializer::SerializeCodeSection() {
+  // Save the number of functions.
+  strm_->Write(static_cast<uint64_t>(vm_->functions.size()));
+  for (const auto& func : vm_->functions) {
+    // Serialize the function info.
+    VMFunctionSerializer func_format(func.name,
+                                     func.register_file_size,
+                                     func.instructions.size(),
+                                     func.params);
+    func_format.Save(strm_);
+
+    // Serialize each instruction.
+    for (const auto& instr : func.instructions) {
+      const auto& serialized_instr = SerializeInstruction(instr);
+      serialized_instr.Save(strm_);
+    }
+  }
+}
+
+tvm::Array<tvm::Expr> Serializer::GetGlobals() const {
+  tvm::Array<tvm::Expr> ret;
+  std::vector<std::pair<std::string, Index> > globals(vm_->global_map.begin(),
+                                                      vm_->global_map.end());
+  auto comp = [](const std::pair<std::string, Index>& a,
+                 const std::pair<std::string, Index>& b) {
+    return a.second < b.second;
+  };
+  std::sort(globals.begin(), globals.end(), comp);
+  for (const auto& it : globals) {
+    ret.push_back(tvm::ir::StringImm::make(it.first));
+  }
+  return ret;
+}
+
+std::string Serializer::GetBytecode() const {
+  std::ostringstream oss;
+
+  for (const auto& func : vm_->functions) {
+    // Print the header of the function format.
+    oss << "# func name, reg file size, param count, inst count:"
+        << std::endl;
+    oss << func.name << " "
+        << func.register_file_size << " "
+        << func.params.size() << " "
+        << func.instructions.size() << std::endl;
+
+    // Print pramams of a `VMFunction`.
+    oss << "# Parameters:"<< std::endl;
+    for (const auto& param : func.params) {
+      oss << param << " ";
+    }
+    oss << std::endl;
+
+    // Print the instructions of a `VMFunction`.
+    // The part after ";" is the instruction in text format.
+    oss << "hash, opcode, fields # inst(text):"<< std::endl;
+    for (const auto& instr : func.instructions) {
+      const auto& serialized_instr = SerializeInstruction(instr);
+      oss << std::hex << "0x" << serialized_instr.Hash() << " "
+          << std::dec << serialized_instr.opcode << " ";
+      for (auto it : serialized_instr.fields) {
+        oss << it << " ";
+      }
+      oss << "  # " << instr;
+      if (oss.str().back() != '\n') oss << std::endl;
+    }
+  }
+
+  return oss.str();
+}
+
+runtime::Module Serializer::GetLib() const {
+  return vm_->lib;
+}
+
+runtime::Module CreateSerializer(const VirtualMachine* vm) {
+  std::shared_ptr<Serializer> exec = std::make_shared<Serializer>();
+  exec->Init(vm);
+  return runtime::Module(exec);
+}
+
+TVM_REGISTER_GLOBAL("relay._vm._Serializer")
+.set_body([](TVMArgs args, TVMRetValue* rv) {
+  runtime::Module mod = args[0];
+  const auto* vm = dynamic_cast<VirtualMachine*>(mod.operator->());
+  CHECK(vm) << "Virtual machine has not been defined yet."
+            << "\n";
+  *rv = CreateSerializer(vm);
+});
+
+}  // namespace vm
+}  // namespace relay
+}  // namespace tvm
diff --git a/src/relay/backend/vm/serializer.h b/src/relay/backend/vm/serializer.h
new file mode 100644
index 000000000000..2371bb4c94f5
--- /dev/null
+++ b/src/relay/backend/vm/serializer.h
@@ -0,0 +1,202 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ *  Copyright (c) 2019 by Contributors
+ * \file src/relay/backend/vm/serializer.h
+ * \brief Define a serializer for the Relay VM.
+ *
+ * The following components of a Relay VM will be serialized:
+ *  - The `constants`, e.g., the constant pool, that contains the
+ *  constants used in a Relay program.
+ *  - The `packed_funcs` that essentially contains the generated code for
+ *  a specific target. We return it as a runtime module that can be exported as
+ *  a library file (e.g., .so, .o, or .tar).
+ *  - The `global_map` that contains the globals.
+ *  - The `primitive_map` that contains the name of individual primitive operators.
+ *  - The `functions`, e.g., the `VMFunction`. Each `VMFunction` is composed of
+ *  a list of instructions/bytecode.
+ *
+ * Note that only the library is returned as a separate module. All othere parts
+ * are stored in a single serialized code that is organized with the following
+ * sections in order.
+ *  - Global section, containing all globals.
+ *  - Constant section, storing the constant pool.
+ *  - Primitive name section, containing the function name of the primitive ops
+ *  used by the virtual machine.
+ *  - Code section, handling the VM functions and bytecode.
+ *
+ * The code section is again organized as follows for each VM function:
+ *   func_name, register_file_size, num_instructions (N)
+ *   param1, param2, ..., paramM
+ *   instruction1
+ *   instruction2
+ *   ...
+ *   instructionN
+ *
+ * Serializing an `Instruction` requires us to deal with the bytecode. Each line
+ * of the instructions could be serialized as the following format:
+ *   hash, opcode, f1, f2, ..., fX, field with variable length
+ *   1. hash: the hash of the instruction. This number will be used to help us
+ * validate if an instruction is well-formed during deserialization.
+ *   2. opcode: the opcode code of the instruction.
+ *   3. f1, f2, ..., fX. These fields together represent the fixed fields in
+ * an instruction, e.g., `from` and `dst` fields of a `Move` instruction. For
+ * example, `DLDataType` will be unpacked into three fields (code, bits, lanes).
+ *   4. The rest of the line indicates the field with variable length, e.g.,
+ * the shape of a tensor, the args used by an `InvokPacked` instruction, etc.
+ */
+
+#ifndef TVM_RELAY_BACKEND_VM_SERIALIZER_H_
+#define TVM_RELAY_BACKEND_VM_SERIALIZER_H_
+
+#include <dmlc/io.h>
+#include <dmlc/memory_io.h>
+#include <tvm/ir.h>
+#include <tvm/node/container.h>
+#include <tvm/packed_func_ext.h>
+#include <tvm/runtime/packed_func.h>
+#include <tvm/runtime/vm.h>
+
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+namespace tvm {
+namespace relay {
+namespace vm {
+
+using namespace tvm::runtime;
+using namespace tvm::runtime::vm;
+
+/*!
+ * \brief The Relay VM serializer.
+ */
+class Serializer : public runtime::ModuleNode {
+ public:
+  /*!
+   * \brief Initialize the serializer for a virtual machine.
+   *
+   *  \param vm The Relay virtual machine.
+   */
+  inline void Init(const VirtualMachine* vm);
+
+  /*!
+   * \brief Return the member function to the frontend.
+   *
+   * \param name The name of the function.
+   * \param sptr_to_self The pointer to the module node.
+   *
+   * \return The corresponding member function.
+   */
+  PackedFunc GetFunction(const std::string& name,
+                         const std::shared_ptr<ModuleNode>& sptr_to_self) final;
+
+  const char* type_key() const final { return "Serializer"; }
+
+  /*!
+   * \brief Print the detailed statistics of the given code, i.e. number of
+   * globls and constants, etc.
+   */
+  std::string Stats() const;
+
+  /*!
+   * \brief Serialize the `vm_` into global section, constant section, and code
+   * section.
+   *
+   * \return The binary representation of the VM.
+   */
+  TVMByteArray Serialize();
+
+  /*!
+   * \brief Get a list of the globals used by the `_vm`.
+   *
+   * \return The global map in the form a list.
+   */
+  tvm::Array<tvm::Expr> GetGlobals() const;
+
+  /*!
+   * \brief Get the primitive operators that are contained in the Relay VM.
+   *
+   * \return The list of primitve operators.
+   */
+  tvm::Array<tvm::Expr> GetPrimitiveOps() const;
+
+  /*!
+   * \brief Get the serialized form of the `functions` in `vm_`. This is
+   * essentially bytecode serialization.
+   *
+   * \return The serialized vm bytecode.
+   *
+   * \note The bytecode is in the following format:
+   *   func_name reg_file_size num_instructions
+   *   param1 param2 ... paramM
+   *   instruction1
+   *   instruction2
+   *   ...
+   *   instructionN
+   *
+   * Each instruction is printed in the following format:
+   *   opcode num_fields field1 ... fieldX # The text format.
+   *
+   * The field starting from # is only used for debugging. The serialized code
+   * doesn't contain it, therefore the deserializer doens't need to handle it.
+   */
+  std::string GetBytecode() const;
+
+  /*! \brief Get the `lib` module in vm_. Serialization of `runtime::module`
+   * has already been supported by TVM. Therefore, we only return the runtime
+   * module and let users have the flexibility to call `export_library` from
+   * the frontend to save the library to disk.
+   *
+   * \return The runtime module that contains the hardwre dependent code.
+   */
+  inline runtime::Module GetLib() const;
+
+  virtual ~Serializer() { delete strm_; }
+
+ private:
+  /*! \brief Serialize the globals in vm_. */
+  void SerializeGlobalSection();
+
+  /*! \brief Serialize the constant pool in vm_. */
+  void SerializeConstantSection();
+
+  /*! \brief Serialize primitive op names in vm_. */
+  void SerializePrimitiveOpNames();
+
+  /*! \brief Serialize the vm functions in vm_. */
+  void SerializeCodeSection();
+
+  /*! \brief The Relay virtual machine for to be serialized. */
+  const VirtualMachine* vm_;
+
+  /*! \brief The stream used for serialization. */
+  dmlc::Stream* strm_;
+
+  /*! \brief The serialized code. */
+  std::string code_;
+};
+
+}  // namespace vm
+}  // namespace relay
+}  // namespace tvm
+
+#endif  // TVM_RELAY_BACKEND_VM_SERIALIZER_H_
diff --git a/src/runtime/vm/vm.cc b/src/runtime/vm/vm.cc
index b79c45526941..e9b567bed584 100644
--- a/src/runtime/vm/vm.cc
+++ b/src/runtime/vm/vm.cc
@@ -23,6 +23,7 @@
  * \brief The Relay virtual machine.
  */
 
+#include <dmlc/memory_io.h>
 #include <tvm/logging.h>
 #include <tvm/runtime/vm.h>
 
@@ -91,8 +92,8 @@ Instruction::Instruction(const Instruction& instr) {
       return;
     case Opcode::InvokeClosure:
       this->closure = instr.closure;
-      this->closure_args_num = instr.closure_args_num;
-      this->closure_args = Duplicate<RegName>(instr.closure_args, instr.closure_args_num);
+      this->num_closure_args = instr.num_closure_args;
+      this->closure_args = Duplicate<RegName>(instr.closure_args, instr.num_closure_args);
       return;
     case Opcode::Invoke:
       this->func_index = instr.func_index;
@@ -179,9 +180,9 @@ Instruction& Instruction::operator=(const Instruction& instr) {
       return *this;
     case Opcode::InvokeClosure:
       this->closure = instr.closure;
-      this->closure_args_num = instr.closure_args_num;
+      this->num_closure_args = instr.num_closure_args;
       FreeIf(this->closure_args);
-      this->closure_args = Duplicate<RegName>(instr.closure_args, instr.closure_args_num);
+      this->closure_args = Duplicate<RegName>(instr.closure_args, instr.num_closure_args);
       return *this;
     case Opcode::Invoke:
       this->func_index = instr.func_index;
@@ -262,7 +263,9 @@ Instruction Instruction::Fatal() {
   return instr;
 }
 
-Instruction Instruction::InvokePacked(Index packed_index, Index arity, Index output_size,
+Instruction Instruction::InvokePacked(Index packed_index,
+                                      Index arity,
+                                      Index output_size,
                                       const std::vector<RegName>& args) {
   Instruction instr;
   instr.op = Opcode::InvokePacked;
@@ -380,7 +383,7 @@ Instruction Instruction::InvokeClosure(RegName closure, const std::vector<RegNam
   instr.op = Opcode::InvokeClosure;
   instr.dst = dst;
   instr.closure = closure;
-  instr.closure_args_num = args.size();
+  instr.num_closure_args = args.size();
   instr.closure_args = new RegName[args.size()];
   for (size_t i = 0; i < args.size(); ++i) {
     instr.closure_args[i] = args[i];
@@ -396,7 +399,7 @@ Instruction Instruction::LoadConst(Index const_index, RegName dst) {
   return instr;
 }
 
-Instruction Instruction::LoadConsti(size_t val, RegName dst) {
+Instruction Instruction::LoadConsti(Index val, RegName dst) {
   Instruction instr;
   instr.op = Opcode::LoadConsti;
   instr.dst = dst;
@@ -432,7 +435,7 @@ void DLDatatypePrint(std::ostream& os, const DLDataType& dtype) {
 }
 
 template<typename T>
-std::string StrJoin(T* items, int offset, int cnt, std::string delim = ",") {
+std::string StrJoin(T* items, int offset, int cnt, std::string delim = ", ") {
   if (cnt == 0) {
     return "";
   }
@@ -447,11 +450,11 @@ std::string StrJoin(T* items, int offset, int cnt, std::string delim = ",") {
 void InstructionPrint(std::ostream& os, const Instruction& instr) {
   switch (instr.op) {
     case Opcode::Move: {
-      os << "move $" << instr.dst << " $" << instr.from;
+      os << "move $" << instr.dst << " $" << instr.from << std::endl;
       break;
     }
     case Opcode::Ret: {
-      os << "ret $" << instr.result;
+      os << "ret $" << instr.result  << std::endl;
       break;
     }
     case Opcode::Fatal: {
@@ -459,74 +462,86 @@ void InstructionPrint(std::ostream& os, const Instruction& instr) {
       break;
     }
     case Opcode::InvokePacked: {
-      os << "invoke_packed PackedFunc[" << instr.packed_index << "](in: $"
-         << StrJoin<RegName>(instr.packed_args, 0, instr.arity - instr.output_size, ",$")
+      os << "invoke_packed PackedFunc[" << instr.packed_index << "] (in: $"
+         << StrJoin<RegName>(instr.packed_args, 0,
+                             instr.arity - instr.output_size, ", $")
          << ", out: $"
          << StrJoin<RegName>(instr.packed_args, instr.arity - instr.output_size,
-                 instr.output_size, ",$")
-         << ")";
+                             instr.output_size, ", $")
+         << ")" << std::endl;
       break;
     }
     case Opcode::AllocTensor: {
       os << "alloc_tensor $" << instr.dst << " ["
-         << StrJoin<int64_t>(instr.alloc_tensor.shape, 0, instr.alloc_tensor.ndim)
+         << StrJoin<int64_t>(instr.alloc_tensor.shape, 0,
+                             instr.alloc_tensor.ndim)
          << "] ";
       DLDatatypePrint(os, instr.alloc_tensor.dtype);
+      os << std::endl;
       break;
     }
     case Opcode::AllocTensorReg: {
       os << "alloc_tensor_reg $" << instr.dst << " $"
          << instr.alloc_tensor_reg.shape_register << " ";
       DLDatatypePrint(os, instr.alloc_tensor_reg.dtype);
+      os << std::endl;
       break;
     }
     case Opcode::AllocDatatype: {
       os << "alloc_data $" << instr.dst << " tag(" << instr.constructor_tag << ") [$"
-         << StrJoin<RegName>(instr.datatype_fields, 0, instr.num_fields, ",$") << "]";
+         << StrJoin<RegName>(instr.datatype_fields, 0, instr.num_fields, ",$") << "]"
+         << std::endl;
       break;
     }
     case Opcode::AllocClosure: {
       os << "alloc_closure $" << instr.dst << " VMFunc[" << instr.clo_index
          << "]($" << StrJoin<RegName>(instr.free_vars, 0, instr.num_freevar, ",$")
-         << ")";
+         << ")"
+         << std::endl;
       break;
     }
     case Opcode::If: {
       os << "if " << "$" << instr.if_op.test << " " << instr.if_op.target << " "
-         << instr.if_op.true_offset << " " << instr.if_op.false_offset;
+         << instr.if_op.true_offset << " " << instr.if_op.false_offset
+         << std::endl;
       break;
     }
     case Opcode::Invoke: {
       os << "invoke $" << instr.dst << " VMFunc[" << instr.func_index << "]($"
          << StrJoin<RegName>(instr.invoke_args_registers, 0, instr.num_args, ",$")
-         << ")";
+         << ")"
+         << std::endl;
       break;
     }
     case Opcode::InvokeClosure: {
       os << "invoke_closure $" << instr.dst << " $" << instr.closure << "($"
-         << StrJoin<RegName>(instr.closure_args, 0, instr.closure_args_num, ",$")
-         << ")";
+         << StrJoin<RegName>(instr.closure_args, 0, instr.num_closure_args, ",$")
+         << ")"
+         << std::endl;
       break;
     }
     case Opcode::LoadConst: {
-      os << "load_const $" << instr.dst << " Const[" << instr.const_index << "]";
+      os << "load_const $" << instr.dst << " Const[" << instr.const_index << "]"
+         << std::endl;
       break;
     }
     case Opcode::LoadConsti: {
-      os << "load_consti $" << instr.dst << " Const[" << instr.load_consti.val << "]";
+      os << "load_consti $" << instr.dst << " Const[" << instr.load_consti.val << "]"
+         << std::endl;
       break;
     }
     case Opcode::GetField: {
       os << "get_field $" << instr.dst << " $" << instr.object << "["
-         << instr.field_index << "]";
+         << instr.field_index << "]"
+         << std::endl;
       break;
     }
     case Opcode::GetTag: {
-      os << "get_tag $" << instr.dst << " $" << instr.get_tag.object;
+      os << "get_tag $" << instr.dst << " $" << instr.get_tag.object << std::endl;
       break;
     }
     case Opcode::Goto: {
-      os << "goto " << instr.pc_offset;
+      os << "goto " << instr.pc_offset << std::endl;
       break;
     }
     default:
@@ -564,6 +579,23 @@ PackedFunc VirtualMachine::GetFunction(const std::string& name,
         Object obj = args[i];
         func_args.push_back(obj);
       }
+      auto it = std::find_if(functions.begin(), functions.end(),
+                             [func_name](const VMFunction& func) {
+                               return func.name == func_name;
+                             });
+      CHECK(it != functions.end()) << "Cannot find function " << func_name << "\n";
+      CHECK_EQ(func_args.size() + params_.size(), it->params.size())
+          << "The number of provided parameters doesn't match the number of arguments"
+          << "\n";
+      if (!params_.empty()) {
+        for (const auto& p : it->params) {
+          const auto& pit = params_.find(p);
+          if (pit != params_.end()) {
+            func_args.push_back(pit->second);
+          }
+        }
+        CHECK_EQ(func_args.size(), it->params.size());
+      }
       *rv = this->Invoke(func_name, func_args);
     });
   } else if (name == "init") {
@@ -579,12 +611,40 @@ PackedFunc VirtualMachine::GetFunction(const std::string& name,
       }
       this->Init(contexts);
     });
+  } else if (name == "load_params") {
+    return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+      this->LoadParams(args[0].operator std::string());
+    });
   } else {
     LOG(FATAL) << "Unknown packed function: " << name;
     return PackedFunc([sptr_to_self, name](TVMArgs args, TVMRetValue* rv) {});
   }
 }
 
+void VirtualMachine::LoadParams(const std::string& params) {
+  dmlc::MemoryStringStream mss(const_cast<std::string*>(&params));
+  dmlc::Stream* strm = &mss;
+  uint64_t header, reserved;
+  CHECK(strm->Read(&header)) << "Invalid parameter file";
+  CHECK(header == kTVMNDArrayListMagic) << "Invalid parameter file";
+  CHECK(strm->Read(&reserved)) << "Invalid parameter file";
+
+  std::vector<std::string> names;
+  CHECK(strm->Read(&names)) << "Invalid parameter file";
+
+  uint64_t sz;
+  strm->Read(&sz);
+  size_t size = static_cast<size_t>(sz);
+  CHECK(size == names.size()) << "Invalid parameter file";
+
+  for (size_t i = 0; i < size; i++) {
+    NDArray arr;
+    CHECK(arr.Load(strm)) << "Invalid parameter file";
+    runtime::Object obj = runtime::Object::Tensor(arr);
+    params_.emplace(std::make_pair(names[i], obj));
+  }
+}
+
 void VirtualMachine::PushFrame(Index arg_count, Index ret_pc, const VMFunction& vm_func) {
   auto frame = VMFrame(ret_pc, func_index, arg_count, code, vm_func.register_file_size);
   frames.push_back(frame);
@@ -662,7 +722,22 @@ void InvokePacked(const PackedFunc& func, Index arg_count, Index output_size,
   func.CallPacked(TVMArgs(values.data(), codes.data(), arity), &rv);
 }
 
-void VirtualMachine::Init(const std::vector<TVMContext>& ctxs) { this->ctxs = ctxs; }
+void VirtualMachine::Init(const std::vector<TVMContext>& ctxs) {
+  this->ctxs = ctxs;
+
+  // Get the list of packed functions.
+  CHECK(primitive_map.empty() || lib.operator->())
+      << "runtime module should have been built for primitive functions"
+      << "\n";
+  for (const auto& it : primitive_map) {
+    const auto& packed_name = it.first;
+    auto packed_index = static_cast<size_t>(it.second);
+    if (packed_funcs.size() <= packed_index) {
+      packed_funcs.resize(packed_index + 1);
+    }
+    packed_funcs[packed_index] = lib.GetFunction(packed_name);
+  }
+}
 
 inline void VirtualMachine::WriteRegister(Index r, const Object& val) {
   frames.back().register_file[r] = val;
@@ -716,8 +791,8 @@ void VirtualMachine::Run() {
         goto main_loop;
       }
       case Opcode::LoadConsti: {
-        auto tensor = NDArray::Empty({1}, {kDLInt, 32, 1}, {kDLCPU, 0});
-        reinterpret_cast<int32_t*>(tensor->data)[0] = instr.load_consti.val;
+        auto tensor = NDArray::Empty({1}, {kDLInt, 64, 1}, {kDLCPU, 0});
+        reinterpret_cast<int64_t*>(tensor->data)[0] = instr.load_consti.val;
         WriteRegister(instr.dst, Object::Tensor(tensor));
         pc++;
         goto main_loop;
@@ -753,7 +828,7 @@ void VirtualMachine::Run() {
         for (auto free_var : closure->free_vars) {
           args.push_back(free_var);
         }
-        for (Index i = 0; i < instr.closure_args_num; ++i) {
+        for (Index i = 0; i < instr.num_closure_args; ++i) {
           args.push_back(ReadRegister(instr.closure_args[i]));
         }
         InvokeGlobal(this->functions[closure->func_index], args);
diff --git a/tests/python/relay/test_vm_serialization.py b/tests/python/relay/test_vm_serialization.py
new file mode 100644
index 000000000000..9a8ab2d87444
--- /dev/null
+++ b/tests/python/relay/test_vm_serialization.py
@@ -0,0 +1,356 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+# pylint: disable=invalid-name, missing-docstring, no-else-return
+"""Unit tests for the Relay VM serialization and deserialization."""
+import numpy as np
+
+import tvm
+from tvm import relay
+from tvm.relay.module import Module as rly_module
+from tvm.relay import vm as _vm
+from tvm.relay import serializer, deserializer
+from tvm.relay.scope_builder import ScopeBuilder
+from tvm.relay.prelude import Prelude
+from tvm.contrib import util
+from tvm.relay import testing
+
+def create_vm(f, ctx=tvm.cpu(), target="llvm"):
+    if isinstance(f, relay.Expr):
+        mod = relay.Module()
+        mod["main"] = f
+        compiler = relay.vm.VMCompiler()
+        vm = compiler.compile(mod, target)
+        vm.init(ctx)
+        return vm
+    else:
+        assert isinstance(f, relay.Module), "expected mod as relay.Module"
+        compiler = relay.vm.VMCompiler()
+        vm = compiler.compile(f, target)
+        vm.init(ctx)
+        return vm
+
+
+def veval(vm, *args, ctx=tvm.cpu()):
+    assert isinstance(vm, _vm.VirtualMachine), "expected VirtualMachine"
+    vm.init(ctx)
+    ret = vm.run(*args)
+    return ret
+
+
+def run_network(mod,
+                params,
+                data_shape=(1, 3, 224, 224),
+                dtype='float32'):
+    def get_vm_output(mod, data, params, target, ctx, dtype='float32'):
+        ex = relay.create_executor('vm', mod=mod, ctx=ctx)
+        result = ex.evaluate()(data, **params)
+        return result.asnumpy().astype(dtype)
+
+    def get_serialized_output(mod, data, params, target, ctx, dtype='float32'):
+        vm = create_vm(mod, ctx, target)
+        ser = serializer.Serializer(vm)
+        code, lib = ser.serialize()
+        deser = deserializer.Deserializer(code, lib)
+        des_vm = deser.deserialize()
+        des_vm.init(ctx)
+        des_vm.load_params(params)
+        result = des_vm.run(data)
+        return result.asnumpy().astype(dtype)
+
+    data = np.random.uniform(size=data_shape).astype(dtype)
+    target = "llvm"
+    ctx = tvm.cpu(0)
+
+    tvm_out = get_vm_output(mod, tvm.nd.array(data.astype(dtype)), params,
+                            target, ctx, dtype)
+    vm_out = get_serialized_output(mod, tvm.nd.array(data.astype(dtype)), params,
+                                   target, ctx, dtype)
+    tvm.testing.assert_allclose(vm_out, tvm_out, rtol=1e-5, atol=1e-5)
+
+
+def test_serializer():
+    mod = rly_module({})
+    a = relay.const(1.0, "float32")
+    x = relay.var('x', shape=(10, 10), dtype='float32')
+    f1 = relay.Function([x], x + a)
+    glb_f1 = relay.GlobalVar("f1")
+    mod[glb_f1] = f1
+
+    b = relay.const(2.0, "float32")
+    y = relay.var('y', shape=(10, 10), dtype='float32')
+    f2 = relay.Function([y], y - b)
+    glb_f2 = relay.GlobalVar("f2")
+    mod[glb_f2] = f2
+
+    x1 = relay.var('x1', shape=(10, 10), dtype='float32')
+    y1 = relay.var('y1', shape=(10, 10), dtype='float32')
+    main = relay.Function([x1, y1], glb_f1(x1) * glb_f2(y1))
+    mod["main"] = main
+
+    vm = create_vm(mod)
+    ser = serializer.Serializer(vm)
+
+    stats = ser.stats
+    assert "scalar" in stats
+
+    glbs = ser.globals
+    assert len(glbs) == 3
+    assert "f1" in glbs
+    assert "f2" in glbs
+    assert "main" in glbs
+
+    prim_ops = ser.primitive_ops
+    assert any(item.startswith('fused_add') for item in prim_ops)
+    assert any(item.startswith('fused_subtract') for item in prim_ops)
+    assert any(item.startswith('fused_multiply') for item in prim_ops)
+
+    code = ser.bytecode
+    assert "main 5 2 5" in code
+    assert "f1 3 1 4" in code
+    assert "f2 3 1 4" in code
+
+    code, lib = ser.serialize()
+    assert isinstance(code, bytearray)
+    assert isinstance(lib, tvm.module.Module)
+
+
+def test_save_load():
+    x = relay.var('x', shape=(10, 10))
+    f = relay.Function([x], x + x)
+    x_data = np.random.rand(10, 10).astype('float32')
+
+    # serialize.
+    vm = create_vm(f)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    assert isinstance(code, bytearray)
+
+    # save and load the code and lib file.
+    tmp = util.tempdir()
+    path_lib = tmp.relpath("lib.so")
+    lib.export_library(path_lib)
+    with open(tmp.relpath("code.bc"), "wb") as fo:
+        fo.write(code)
+
+    loaded_lib = tvm.module.load(path_lib)
+    loaded_code = bytearray(open(tmp.relpath("code.bc"), "rb").read())
+
+    # deserialize.
+    deser = deserializer.Deserializer(loaded_code, loaded_lib)
+    des_vm = deser.deserialize()
+
+    res = veval(des_vm, x_data)
+    tvm.testing.assert_allclose(res.asnumpy(), x_data + x_data)
+
+
+def test_const():
+    c = relay.const(1.0, "float32")
+    x = relay.var('x', shape=(10, 10), dtype='float32')
+    f = relay.Function([x], x + c)
+    vm = create_vm(f)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    assert isinstance(code, bytearray)
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+    x_data = np.random.rand(10, 10).astype('float32')
+    res = veval(des_vm, x_data)
+    tvm.testing.assert_allclose(res.asnumpy(), x_data + 1)
+
+
+def test_if():
+    x = relay.var('x', shape=(10, 10))
+    y = relay.var('y', shape=(10, 10))
+    equal = relay.op.equal(x, y)
+    equal = relay.op.nn.batch_flatten(equal)
+    f = relay.Function([x, y], relay.If(relay.op.min(equal, axis=[0, 1]), x,
+                                        y))
+    x_data = np.random.rand(10, 10).astype('float32')
+    y_data = np.random.rand(10, 10).astype('float32')
+
+    vm = create_vm(f)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    # same
+    res = veval(des_vm, x_data, x_data)
+    tvm.testing.assert_allclose(res.asnumpy(), x_data)
+
+    # diff
+    res = veval(des_vm, x_data, y_data)
+    tvm.testing.assert_allclose(res.asnumpy(), y_data)
+
+
+def test_loop():
+    mod = relay.module.Module({})
+    sum_up = relay.GlobalVar('sum_up')
+    i = relay.var('i', shape=[], dtype='int32')
+    accum = relay.var('accum', shape=[], dtype='int32')
+    sb = ScopeBuilder()
+    with sb.if_scope(relay.equal(i, relay.const(0, 'int32'))):
+        sb.ret(accum)
+    with sb.else_scope():
+        one_less = relay.subtract(i, relay.const(1, 'int32'))
+        new_accum = relay.add(accum, i)
+        sb.ret(relay.Call(sum_up, [one_less, new_accum]))
+    func = relay.Function([i, accum], sb.get())
+    mod[sum_up] = func
+    loop_bound = 0
+    i_data = np.array(loop_bound, dtype='int32')
+    accum_data = np.array(0, dtype='int32')
+    iarg = relay.var('i', shape=[], dtype='int32')
+    aarg = relay.var('accum', shape=[], dtype='int32')
+    mod["main"] = relay.Function([iarg, aarg], sum_up(iarg, aarg))
+
+    vm = create_vm(mod)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    result = veval(des_vm, i_data, accum_data)
+    tvm.testing.assert_allclose(result.asnumpy(), sum(range(1, loop_bound + 1)))
+
+
+def test_tuple():
+    ttype = relay.TupleType([relay.TensorType((1,)), relay.TensorType((10,))])
+    tup = relay.var('tup', type_annotation=ttype)
+    f = relay.Function([tup], relay.TupleGetItem(tup, 1))
+    i_data = np.random.rand(41).astype('float32')
+    j_data = np.random.rand(10).astype('float32')
+
+    vm = create_vm(f)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    result = veval(des_vm, (i_data, j_data))
+    tvm.testing.assert_allclose(result.asnumpy(), j_data)
+
+
+def test_adt_list():
+    mod = relay.Module()
+    p = Prelude(mod)
+
+    l1 = p.cons(relay.const(1), p.nil())
+    l21 = p.cons(relay.const(2), l1)
+    l321 = p.cons(relay.const(3), l21)
+
+    f = relay.Function([], l321)
+    mod["main"] = f
+
+    vm = create_vm(mod)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    result = veval(des_vm)
+    assert len(result) == 2
+    assert len(result[1]) == 2
+    assert len(result[1][1]) == 2
+    res = []
+    res.append(result[0].asnumpy().tolist())
+    res.append(result[1][0].asnumpy().tolist())
+    res.append(result[1][1][0].asnumpy().tolist())
+    tvm.testing.assert_allclose(res, np.array([3, 2, 1]))
+
+
+def test_adt_compose():
+    mod = relay.Module()
+    p = Prelude(mod)
+
+    compose = p.compose
+
+    # add_one = fun x -> x + 1
+    sb = relay.ScopeBuilder()
+    x = relay.var('x', 'float32')
+    x1 = sb.let('x1', x)
+    xplusone = x1 + relay.const(1.0, 'float32')
+    sb.ret(xplusone)
+    body = sb.get()
+    add_one = relay.GlobalVar("add_one")
+    add_one_func = relay.Function([x], body)
+
+    # add_two = compose(add_one, add_one)
+    sb = relay.ScopeBuilder()
+    y = relay.var('y', 'float32')
+    add_two_func = sb.let('add_two', compose(add_one_func, add_one_func))
+    add_two_res = add_two_func(y)
+    sb.ret(add_two_res)
+    add_two_body = sb.get()
+
+    mod[add_one] = add_one_func
+
+    f = relay.Function([y], add_two_body)
+    mod["main"] = f
+
+    vm = create_vm(mod)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    x_data = np.array(np.random.rand()).astype('float32')
+    result = veval(des_vm, x_data)
+
+    tvm.testing.assert_allclose(result.asnumpy(), x_data + 2.0)
+
+
+def test_closure():
+    x = relay.var('x', shape=())
+    y = relay.var('y', shape=())
+    f = relay.Function([x], x + y)
+    ff = relay.Function([y], f)
+    clo = ff(relay.const(1.0))
+    main = clo(relay.const(2.0))
+
+    vm = create_vm(main)
+    ser = serializer.Serializer(vm)
+    code, lib = ser.serialize()
+    deser = deserializer.Deserializer(code, lib)
+    des_vm = deser.deserialize()
+
+    res = veval(des_vm)
+    tvm.testing.assert_allclose(res.asnumpy(), 3.0)
+
+
+def test_resnet():
+    mod, params = testing.resnet.get_workload(batch_size=1, num_layers=18)
+    run_network(mod, params)
+
+
+def test_mobilenet():
+    mod, params = testing.mobilenet.get_workload(batch_size=1)
+    run_network(mod, params)
+
+
+if __name__ == "__main__":
+    test_serializer()
+    test_save_load()
+    test_const()
+    test_if()
+    test_loop()
+    test_tuple()
+    test_adt_list()
+    test_adt_compose()
+    test_closure()
+    test_resnet()
+    test_mobilenet()