diff --git a/onnxscript/_internal/builder.py b/onnxscript/_internal/builder.py
index 1dc0875871..fc0267271e 100644
--- a/onnxscript/_internal/builder.py
+++ b/onnxscript/_internal/builder.py
@@ -229,6 +229,8 @@ def __init__(self, graph: ir.Graph) -> None:
         # and allows sharing them across different layers/contexts.
         self._constant_cache: dict[tuple[Any, ir.DataType | None], ir.Value] = {}
 
+        self._functions: dict[ir.OperatorIdentifier, ir.Function] = {}
+
     def opset(self, domain: str, version: int = 1) -> OpBuilder:
         """Create an OpBuilder bound to the given domain and version."""
         return OpBuilder(self, domain, version)
@@ -241,6 +243,10 @@ def op(self) -> OpBuilder:
     def graph(self) -> ir.Graph:
         return self._graph
 
+    @property
+    def functions(self) -> dict[ir.OperatorIdentifier, ir.Function]:
+        return self._functions
+
     def initializer(
         self, tensor: ir.TensorProtocol, name: str | None = None, *, qualify: bool = True
     ) -> ir.Value:
@@ -543,16 +549,18 @@ def call_op(
 
     def call(
         self,
-        function,
+        function: ir.Function | onnxscript.OnnxFunction,
         *args,
         _outputs: Sequence[str] | None = None,
         _prefix: str = "",
+        _inline: bool = True,
         **kwargs,
     ):
         if isinstance(function, ir.Function):
             graph = function.graph
         elif isinstance(function, onnxscript.OnnxFunction):
             graph = function.graph()
+            function = function.function_ir
         else:
             raise TypeError("Function must be an ir.Function or onnxscript.OnnxFunction")
         output_renaming: dict[str, str] = {}
@@ -567,18 +575,36 @@ def call(
         else:
             for output in graph.outputs:
                 output_renaming[output.name] = self._qualify_value_name(output.name)
-        nodes, outputs = _inliner.instantiate(graph, args, kwargs)
         if _prefix:
             self.push_module(_prefix)
-        for node in nodes:
-            node.name = self._qualify_node_name(node.name)
-            for output in node.outputs:
-                if output.name:
-                    if output.name in output_renaming:
-                        output.name = output_renaming[output.name]
-                    else:
-                        output.name = self._qualify_value_name(output.name)
+
+        if _inline:
+            nodes, outputs = _inliner.instantiate(graph, args, kwargs)
+
+            for node in nodes:
+                node.name = self._qualify_node_name(node.name)
+                for output in node.outputs:
+                    if output.name:
+                        if output.name in output_renaming:
+                            output.name = output_renaming[output.name]
+                        else:
+                            output.name = self._qualify_value_name(output.name)
+                self.add_node(node)
+        else:
+            node = ir.node(
+                op_type=function.name,
+                inputs=args,
+                attributes=kwargs or None,
+                outputs=[
+                    ir.Value(name=output_renaming[output.name]) for output in graph.outputs
+                ],
+                domain=function.domain,
+                name=self._qualify_node_name(function.name),
+            )
+            outputs = node.outputs
             self.add_node(node)
+            self._functions[function.identifier()] = function
+
         if _prefix:
             self.pop_module()
         return outputs if len(outputs) > 1 else outputs[0]
@@ -684,15 +710,19 @@ def __getattr__(self, op_type: str) -> Callable:
     def initializer(self, tensor: ir.TensorProtocol, name: str | None = None) -> ir.Value:
         return self._builder.initializer(tensor, name)
 
+    def functions(self) -> dict[ir.OperatorIdentifier, ir.Function]:
+        return self._builder.functions
+
     def call(
         self,
         function,
         *args,
         _outputs: Sequence[str] | None = None,
         _prefix: str = "",
+        _inline: bool = True,
         **kwargs,
     ):
-        """Call a function and inline it into the graph.
+        """Call a function and optionally inline it into the graph.
 
         Args:
             function: The function to call (ir.Function or onnxscript.OnnxFunction).
@@ -700,11 +730,14 @@ def call(
             _outputs: Optional sequence of output names. If provided, must match the
                 number of function outputs.
             _prefix: Optional prefix for module scoping (e.g., "layers.0").
+            _inline: If True, the function body is inlined into the caller graph instead of being
+                called as a separate node. When False, the function will be added
+                to the ``.functions`` dictionary. Defaults to True.
             **kwargs: Keyword arguments to pass to the function.
 
         Returns:
             The output value(s) from the function call.
         """
         return self._builder.call(
-            function, *args, _outputs=_outputs, _prefix=_prefix, **kwargs
+            function, *args, _outputs=_outputs, _prefix=_prefix, _inline=_inline, **kwargs
         )
diff --git a/onnxscript/_internal/builder_test.py b/onnxscript/_internal/builder_test.py
index f6f301954b..710e61056c 100644
--- a/onnxscript/_internal/builder_test.py
+++ b/onnxscript/_internal/builder_test.py
@@ -848,6 +848,157 @@ def add_mul(X, Y):
 
         self.assertIn("does not match", str(cm.exception))
 
+    def test_call_inline_false_creates_single_function_node(self):
+        """Test that _inline=False creates a single function call node instead of inlining."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def mul_add_relu(X, Y):
+            tmp = X * Y
+            tmp = tmp + X
+            return op.Relu(tmp)
+
+        result = op.call(mul_add_relu, x, y, _inline=False)
+
+        # With _inline=False, only a single node should be created (the function call)
+        nodes = list(op.builder.graph)
+        self.assertEqual(len(nodes), 1)
+
+        node = nodes[0]
+        self.assertEqual(node.op_type, "mul_add_relu")
+        self.assertEqual(list(node.inputs), [x, y])
+
+        # The result should be a single ir.Value
+        self.assertIsInstance(result, ir.Value)
+        self.assertIs(result, node.outputs[0])
+
+    def test_call_inline_false_registers_function(self):
+        """Test that _inline=False registers the function in GraphBuilder.functions."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def simple_add(X, Y):
+            return op.Add(X, Y)
+
+        op.call(simple_add, x, y, _inline=False)
+
+        # The function should be registered
+        self.assertEqual(len(op.builder.functions), 1)
+        registered = next(iter(op.builder.functions.values()))
+        self.assertEqual(registered.name, "simple_add")
+
+    def test_call_inline_true_does_not_register_function(self):
+        """Test that _inline=True (default) does not register the function."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def simple_add(X, Y):
+            return op.Add(X, Y)
+
+        op.call(simple_add, x, y, _inline=True)
+
+        # No function should be registered when inlining
+        self.assertEqual(len(op.builder.functions), 0)
+
+    def test_call_inline_false_with_outputs_option(self):
+        """Test that _inline=False respects the _outputs option for renaming."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def add_mul(X, Y):
+            a = X + Y
+            b = X * Y
+            return a, b
+
+        result = op.call(
+            add_mul, x, y, _outputs=["sum_result", "product_result"], _inline=False
+        )
+
+        # The result should be a sequence of 2 ir.Values
+        self.assertEqual(len(result), 2)
+        sum_result, product_result = result
+
+        # Verify output names
+        self.assertEqual(sum_result.name, "v_sum_result")
+        self.assertEqual(product_result.name, "v_product_result")
+
+        # Only one node (the function call), not inlined
+        nodes = list(op.builder.graph)
+        self.assertEqual(len(nodes), 1)
+        self.assertEqual(nodes[0].op_type, "add_mul")
+
+    def test_call_inline_false_with_prefix_option(self):
+        """Test that _inline=False respects the _prefix option for hierarchical naming."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def mul_add_relu(X, Y):
+            tmp = X * Y
+            tmp = tmp + X
+            return op.Relu(tmp)
+
+        result = op.call(mul_add_relu, x, y, _prefix="layer1", _inline=False)
+
+        nodes = list(op.builder.graph)
+        self.assertEqual(len(nodes), 1)
+
+        # The node name should have the prefix
+        self.assertTrue(
+            nodes[0].name.startswith("layer1/"),
+            f"Node name {nodes[0].name} should start with layer1/",
+        )
+
+        self.assertIsInstance(result, ir.Value)
+
+    def test_call_inline_false_via_op_builder(self):
+        """Test that _inline=False works when called through OpBuilder.call."""
+        op, x, y = _create_builder_with_inputs()
+
+        @script(default_opset=op)
+        def simple_add(X, Y):
+            return op.Add(X, Y)
+
+        # Call through OpBuilder (not GraphBuilder directly)
+        result = op.call(simple_add, x, y, _inline=False)
+
+        # Should produce a single function call node
+        nodes = list(op.builder.graph)
+        self.assertEqual(len(nodes), 1)
+        self.assertEqual(nodes[0].op_type, "simple_add")
+        self.assertIsInstance(result, ir.Value)
+
+        # Function should be registered
+        self.assertEqual(len(op.builder.functions), 1)
+
+    def test_call_inline_true_produces_more_nodes_than_inline_false(self):
+        """Test that inlining produces individual op nodes while non-inlining produces one."""
+        # Inline version
+        op1, x1, y1 = _create_builder_with_inputs()
+
+        @script(default_opset=op1)
+        def mul_add(X, Y):
+            tmp = X * Y
+            return op1.Add(tmp, X)
+
+        op1.call(mul_add, x1, y1, _inline=True)
+        inline_nodes = list(op1.builder.graph)
+
+        # Non-inline version
+        op2, x2, y2 = _create_builder_with_inputs()
+
+        @script(default_opset=op2)
+        def mul_add2(X, Y):
+            tmp = X * Y
+            return op2.Add(tmp, X)
+
+        op2.call(mul_add2, x2, y2, _inline=False)
+        non_inline_nodes = list(op2.builder.graph)
+
+        # Inlining should produce 2 nodes (Mul, Add), non-inlining should produce 1
+        self.assertEqual(len(inline_nodes), 2)
+        self.assertEqual(len(non_inline_nodes), 1)
+        self.assertEqual(non_inline_nodes[0].op_type, "mul_add2")
+
 
 class BuildSubgraphTest(unittest.TestCase):
     """Tests for GraphBuilder.subgraph()."""
diff --git a/onnxscript/_internal/values.py b/onnxscript/_internal/values.py
index 051cb3e686..c3fd1b3dad 100644
--- a/onnxscript/_internal/values.py
+++ b/onnxscript/_internal/values.py
@@ -222,6 +222,10 @@ def __call__(self, *args, **kwargs):
     def name(self) -> str:
         return self._name
 
+    @property
+    def domain(self) -> str:
+        return self._opset.domain
+
     @property
     def opset(self) -> Opset:
         return self._opset