diff --git a/backends/xnnpack/test/tester/tester.py b/backends/xnnpack/test/tester/tester.py
index 1b6f03512bd..019b7a4644f 100644
--- a/backends/xnnpack/test/tester/tester.py
+++ b/backends/xnnpack/test/tester/tester.py
@@ -1,4 +1,5 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
+# Copyright 2024-2025 Arm Limited and/or its affiliates.
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
@@ -627,6 +628,15 @@ def check_node_count(self, input: Dict[Any, int]):
 
         return self
 
+    def visualize(
+        self, reuse_server: bool = True, stage: Optional[str] = None, **kwargs
+    ):
+        # import here to avoid importing model_explorer when it is not needed which is most of the time.
+        from executorch.devtools.visualization import visualize
+
+        visualize(self.get_artifact(stage), reuse_server=reuse_server, **kwargs)
+        return self
+
     def run_method_and_compare_outputs(
         self,
         stage: Optional[str] = None,
diff --git a/devtools/visualization/__init__.py b/devtools/visualization/__init__.py
new file mode 100644
index 00000000000..645cc5d5378
--- /dev/null
+++ b/devtools/visualization/__init__.py
@@ -0,0 +1,11 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+from executorch.devtools.visualization.visualization_utils import (  # noqa: F401
+    ModelExplorerServer,
+    SingletonModelExplorerServer,
+    visualize,
+)
diff --git a/devtools/visualization/visualization_utils.py b/devtools/visualization/visualization_utils.py
new file mode 100644
index 00000000000..a2ee4c60505
--- /dev/null
+++ b/devtools/visualization/visualization_utils.py
@@ -0,0 +1,119 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+import subprocess
+import time
+
+from executorch.exir import EdgeProgramManager, ExecutorchProgramManager
+from model_explorer import config, consts, visualize_from_config  # type: ignore
+from torch.export.exported_program import ExportedProgram
+
+
+class SingletonModelExplorerServer:
+    """Singleton context manager for starting a model-explorer server.
+    If multiple ModelExplorerServer contexts are nested, a single
+    server is still used.
+    """
+
+    server: None | subprocess.Popen = None
+    num_open: int = 0
+    wait_after_start = 2.0
+
+    def __init__(self, open_in_browser: bool = True, port: int | None = None):
+        if SingletonModelExplorerServer.server is None:
+            command = ["model-explorer"]
+            if not open_in_browser:
+                command.append("--no_open_in_browser")
+            if port is not None:
+                command.append("--port")
+                command.append(str(port))
+            SingletonModelExplorerServer.server = subprocess.Popen(command)
+
+    def __enter__(self):
+        SingletonModelExplorerServer.num_open = (
+            SingletonModelExplorerServer.num_open + 1
+        )
+        time.sleep(SingletonModelExplorerServer.wait_after_start)
+        return self
+
+    def __exit__(self, type, value, traceback):
+        SingletonModelExplorerServer.num_open = (
+            SingletonModelExplorerServer.num_open - 1
+        )
+        if SingletonModelExplorerServer.num_open == 0:
+            if SingletonModelExplorerServer.server is not None:
+                SingletonModelExplorerServer.server.kill()
+                try:
+                    SingletonModelExplorerServer.server.wait(
+                        SingletonModelExplorerServer.wait_after_start
+                    )
+                except subprocess.TimeoutExpired:
+                    SingletonModelExplorerServer.server.terminate()
+                SingletonModelExplorerServer.server = None
+
+
+class ModelExplorerServer:
+    """Context manager for starting a model-explorer server."""
+
+    wait_after_start = 2.0
+
+    def __init__(self, open_in_browser: bool = True, port: int | None = None):
+        command = ["model-explorer"]
+        if not open_in_browser:
+            command.append("--no_open_in_browser")
+        if port is not None:
+            command.append("--port")
+            command.append(str(port))
+        self.server = subprocess.Popen(command)
+
+    def __enter__(self):
+        time.sleep(self.wait_after_start)
+
+    def __exit__(self, type, value, traceback):
+        self.server.kill()
+        try:
+            self.server.wait(self.wait_after_start)
+        except subprocess.TimeoutExpired:
+            self.server.terminate()
+
+
+def _get_exported_program(
+    visualizable: ExportedProgram | EdgeProgramManager | ExecutorchProgramManager,
+) -> ExportedProgram:
+    if isinstance(visualizable, ExportedProgram):
+        return visualizable
+    if isinstance(visualizable, (EdgeProgramManager, ExecutorchProgramManager)):
+        return visualizable.exported_program()
+    raise RuntimeError(f"Cannot get ExportedProgram from {visualizable}")
+
+
+def visualize(
+    visualizable: ExportedProgram | EdgeProgramManager | ExecutorchProgramManager,
+    reuse_server: bool = True,
+    no_open_in_browser: bool = False,
+    **kwargs,
+):
+    """Wraps the visualize_from_config call from model_explorer.
+    For convenicence, figures out how to find the exported_program
+    from EdgeProgramManager and ExecutorchProgramManager for you.
+
+    See https://github.com/google-ai-edge/model-explorer/wiki/4.-API-Guide#visualize-pytorch-models
+    for full documentation.
+    """
+    cur_config = config()
+    settings = consts.DEFAULT_SETTINGS
+    cur_config.add_model_from_pytorch(
+        "Executorch",
+        exported_program=_get_exported_program(visualizable),
+        settings=settings,
+    )
+    if reuse_server:
+        cur_config.set_reuse_server()
+    visualize_from_config(
+        cur_config,
+        no_open_in_browser=no_open_in_browser,
+        **kwargs,
+    )
diff --git a/devtools/visualization/visualization_utils_test.py b/devtools/visualization/visualization_utils_test.py
new file mode 100644
index 00000000000..89781ab4f43
--- /dev/null
+++ b/devtools/visualization/visualization_utils_test.py
@@ -0,0 +1,153 @@
+# Copyright 2025 Arm Limited and/or its affiliates.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+import time
+
+import pytest
+import torch
+from executorch.backends.xnnpack.test.tester import Tester
+
+from executorch.devtools.visualization import (
+    ModelExplorerServer,
+    SingletonModelExplorerServer,
+    visualization_utils,
+    visualize,
+)
+from executorch.exir import ExportedProgram
+from model_explorer.config import ModelExplorerConfig  # type: ignore
+
+
+@pytest.fixture
+def server():
+    """Mock relevant calls in visualization.visualize and check that parameters have their expected value."""
+    monkeypatch = pytest.MonkeyPatch()
+    with monkeypatch.context():
+        _called_reuse_server = False
+
+        def mock_set_reuse_server(self):
+            nonlocal _called_reuse_server
+            _called_reuse_server = True
+
+        def mock_add_model_from_pytorch(self, name, exported_program, settings):
+            assert isinstance(exported_program, ExportedProgram)
+
+        def mock_visualize_from_config(cur_config, no_open_in_browser):
+            pass
+
+        monkeypatch.setattr(
+            ModelExplorerConfig, "set_reuse_server", mock_set_reuse_server
+        )
+        monkeypatch.setattr(
+            ModelExplorerConfig, "add_model_from_pytorch", mock_add_model_from_pytorch
+        )
+        monkeypatch.setattr(
+            visualization_utils, "visualize_from_config", mock_visualize_from_config
+        )
+        yield monkeypatch.context
+        assert _called_reuse_server, "Did not call reuse_server"
+
+
+class Linear(torch.nn.Module):
+    def __init__(
+        self,
+        in_features: int,
+        out_features: int = 3,
+        bias: bool = True,
+    ):
+        super().__init__()
+        self.inputs = (torch.randn(5, 10, 25, in_features),)
+        self.fc = torch.nn.Linear(
+            in_features=in_features,
+            out_features=out_features,
+            bias=bias,
+        )
+
+    def get_inputs(self) -> tuple[torch.Tensor]:
+        return self.inputs
+
+    def forward(self, x: torch.Tensor) -> torch.Tensor:
+        return self.fc(x)
+
+
+def test_visualize_manual_export(server):
+    with server():
+        model = Linear(20, 30)
+        exported_program = torch.export.export(model, model.get_inputs())
+        visualize(exported_program)
+        time.sleep(3.0)
+
+
+def test_visualize_exported_program(server):
+    with server():
+        model = Linear(20, 30)
+        (
+            Tester(
+                model,
+                example_inputs=model.get_inputs(),
+            )
+            .export()
+            .visualize()
+        )
+
+
+def test_visualize_to_edge(server):
+    with server():
+        model = Linear(20, 30)
+        (
+            Tester(
+                model,
+                example_inputs=model.get_inputs(),
+            )
+            .export()
+            .to_edge()
+            .visualize()
+        )
+
+
+def test_visualize_partition(server):
+    with server():
+        model = Linear(20, 30)
+        (
+            Tester(
+                model,
+                example_inputs=model.get_inputs(),
+            )
+            .export()
+            .to_edge()
+            .partition()
+            .visualize()
+        )
+
+
+def test_visualize_to_executorch(server):
+    with server():
+        model = Linear(20, 30)
+        (
+            Tester(
+                model,
+                example_inputs=model.get_inputs(),
+            )
+            .export()
+            .to_edge()
+            .partition()
+            .to_executorch()
+            .visualize()
+        )
+
+
+if __name__ == "__main__":
+    """A test to run locally to make sure that the web browser opens up
+    automatically as intended.
+    """
+
+    test_visualize_manual_export(ModelExplorerServer)
+
+    with SingletonModelExplorerServer():
+        test_visualize_manual_export(SingletonModelExplorerServer)
+        test_visualize_exported_program(SingletonModelExplorerServer)
+        test_visualize_to_edge(SingletonModelExplorerServer)
+        test_visualize_partition(SingletonModelExplorerServer)
+        test_visualize_to_executorch(SingletonModelExplorerServer)
diff --git a/install_requirements.py b/install_requirements.py
index 3fca161a2c3..60b61271ed5 100644
--- a/install_requirements.py
+++ b/install_requirements.py
@@ -1,4 +1,5 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
+# Copyright 2024-25 Arm Limited and/or its affiliates.
 # All rights reserved.
 #
 # This source code is licensed under the BSD-style license found in the
@@ -132,7 +133,7 @@ def python_is_compatible():
 # NOTE: If a newly-fetched version of the executorch repo changes the value of
 # NIGHTLY_VERSION, you should re-run this script to install the necessary
 # package versions.
-NIGHTLY_VERSION = "dev20241218"
+NIGHTLY_VERSION = "dev20250104"
 
 # The pip repository that hosts nightly torch packages.
 TORCH_NIGHTLY_URL = "https://download.pytorch.org/whl/nightly/cpu"
@@ -169,6 +170,7 @@ def python_is_compatible():
     "tomli",  # Imported by extract_sources.py when using python < 3.11.
     "wheel",  # For building the pip package archive.
     "zstd",  # Imported by resolve_buck.py.
+    "ai-edge-model-explorer>=0.1.16",  # For visualizing ExportedPrograms
 ]
 
 # Assemble the list of requirements to actually install.