diff --git a/src/lightning_lite/lite.py b/src/lightning_lite/lite.py
index 4a1f4e8004..f148632d63 100644
--- a/src/lightning_lite/lite.py
+++ b/src/lightning_lite/lite.py
@@ -153,6 +153,8 @@ class LightningLite(ABC):
         self._validate_setup(model, optimizers)
         original_model = model
 
+        model = self._precision_plugin.convert_module(model)
+
         if move_to_device:
             model = self._move_model_to_device(model=model, optimizers=list(optimizers))
 
diff --git a/src/lightning_lite/plugins/precision/double.py b/src/lightning_lite/plugins/precision/double.py
index 3de2b422f8..9bbb033b74 100644
--- a/src/lightning_lite/plugins/precision/double.py
+++ b/src/lightning_lite/plugins/precision/double.py
@@ -15,6 +15,7 @@ from contextlib import contextmanager
 from typing import Generator
 
 import torch
+from torch.nn import Module
 
 from lightning_lite.plugins.precision.precision import Precision
 
@@ -24,6 +25,9 @@ class DoublePrecision(Precision):
 
     precision: int = 64
 
+    def convert_module(self, module: Module) -> Module:
+        return module.double()
+
     @contextmanager
     def forward_context(self) -> Generator[None, None, None]:
         """A context manager to change the default tensor type.
diff --git a/src/lightning_lite/plugins/precision/precision.py b/src/lightning_lite/plugins/precision/precision.py
index 0fd1a4c4e1..07ce77b889 100644
--- a/src/lightning_lite/plugins/precision/precision.py
+++ b/src/lightning_lite/plugins/precision/precision.py
@@ -29,6 +29,13 @@ class Precision:
 
     precision: Union[str, int] = 32
 
+    def convert_module(self, module: Module) -> Module:
+        """Convert the module parameters to the precision type this plugin handles.
+
+        This is optional and depends on the precision limitations during optimization.
+        """
+        return module
+
     @contextlib.contextmanager
     def forward_context(self) -> Generator[None, None, None]:
         """A contextmanager for managing model forward/training_step/evaluation_step/predict_step."""
diff --git a/src/pytorch_lightning/CHANGELOG.md b/src/pytorch_lightning/CHANGELOG.md
index 6ed9b7f648..fca1366b1c 100644
--- a/src/pytorch_lightning/CHANGELOG.md
+++ b/src/pytorch_lightning/CHANGELOG.md
@@ -94,6 +94,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - The `MLFlowLogger.finalize()` now sets the status to `FAILED` when an exception occurred in `Trainer`, and sets the status to `FINISHED` on successful completion ([#12292](https://github.com/Lightning-AI/lightning/pull/12292))
 
 
+- It is no longer needed to call `model.double()` when using `precision=64` in Lightning Lite ([#14827](https://github.com/Lightning-AI/lightning/pull/14827))
+
+
 ### Deprecated
 
 - Deprecated `LightningDeepSpeedModule` ([#14000](https://github.com/Lightning-AI/lightning/pull/14000))
diff --git a/tests/tests_lite/plugins/precision/test_double_integration.py b/tests/tests_lite/plugins/precision/test_double_integration.py
index 589cfc90b8..e6ab910347 100644
--- a/tests/tests_lite/plugins/precision/test_double_integration.py
+++ b/tests/tests_lite/plugins/precision/test_double_integration.py
@@ -36,7 +36,6 @@ class DoublePrecisionBoringLite(BoringLite):
         return BoringDoubleModule()
 
     def step(self, model, batch):
-        model.double()  # TODO(lite): this needs to be done automatically in Lite.setup()
         assert model.layer.weight.dtype == model.layer.bias.dtype == torch.float64
         assert model.complex_buffer.dtype == torch.complex64