diff --git a/CHANGELOG.md b/CHANGELOG.md
index 49703527a56f3..412eaf32aacce 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -405,6 +405,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed deprecated `optimizer` argument in `LightningModule.manual_backward()`; Toggling optimizers in manual optimization should be done using `LightningModule.{un}toggle_optimizer()` ([#8287](https://github.com/PyTorchLightning/pytorch-lightning/pull/8287))
 
 
+- Removed DeepSpeed FP16 Exception as FP32 is now supported ([#8462](https://github.com/PyTorchLightning/pytorch-lightning/pull/8462))
+
+
 ### Fixed
 
 - Fixed `lr_scheduler` checkpointed state by calling `update_lr_schedulers` before saving checkpoints ([#7877](https://github.com/PyTorchLightning/pytorch-lightning/pull/7877))
diff --git a/pytorch_lightning/plugins/training_type/deepspeed.py b/pytorch_lightning/plugins/training_type/deepspeed.py
index e704b662fd6ca..d47d4caa0321b 100644
--- a/pytorch_lightning/plugins/training_type/deepspeed.py
+++ b/pytorch_lightning/plugins/training_type/deepspeed.py
@@ -541,7 +541,7 @@ def _format_precision_config(self):
         amp_type = self.lightning_module.trainer.accelerator_connector.amp_type
         amp_level = self.lightning_module.trainer.accelerator_connector.amp_level
         precision = self.lightning_module.trainer.accelerator_connector.precision
-        if precision == 16:
+        if precision in (16, 'mixed'):
             if "fp16" not in self.config and amp_type == AMPType.NATIVE:
                 # FP16 is a DeepSpeed standalone AMP implementation
                 rank_zero_info("Enabling DeepSpeed FP16.")
@@ -559,8 +559,6 @@ def _format_precision_config(self):
                     "enabled": True,
                     "opt_level": amp_level,
                 }
-        if "zero_optimization" in self.config and not ("amp" in self.config or "fp16" in self.config):
-            raise MisconfigurationException("To use DeepSpeed ZeRO Optimization, you must set precision=16.")
 
     def _create_default_config(
         self,
diff --git a/tests/plugins/test_deepspeed_plugin.py b/tests/plugins/test_deepspeed_plugin.py
index f3d89b54ae236..dea6bd141dfa1 100644
--- a/tests/plugins/test_deepspeed_plugin.py
+++ b/tests/plugins/test_deepspeed_plugin.py
@@ -164,13 +164,14 @@ def test_deepspeed_plugin_env(tmpdir, monkeypatch, deepspeed_config):
 
 
 @RunIf(amp_native=True, deepspeed=True)
+@pytest.mark.parametrize("precision", [16, 'mixed'])
 @pytest.mark.parametrize(
     "amp_backend", [
         pytest.param("native", marks=RunIf(amp_native=True)),
         pytest.param("apex", marks=RunIf(amp_apex=True)),
     ]
 )
-def test_deepspeed_precision_choice(amp_backend, tmpdir):
+def test_deepspeed_precision_choice(amp_backend, precision, tmpdir):
     """
     Test to ensure precision plugin is also correctly chosen.
     DeepSpeed handles precision via Custom DeepSpeedPrecisionPlugin
@@ -181,12 +182,12 @@ def test_deepspeed_precision_choice(amp_backend, tmpdir):
         default_root_dir=tmpdir,
         plugins='deepspeed',
         amp_backend=amp_backend,
-        precision=16,
+        precision=precision,
     )
 
     assert isinstance(trainer.accelerator.training_type_plugin, DeepSpeedPlugin)
     assert isinstance(trainer.accelerator.precision_plugin, DeepSpeedPrecisionPlugin)
-    assert trainer.accelerator.precision_plugin.precision == 16
+    assert trainer.accelerator.precision_plugin.precision == precision
 
 
 @RunIf(deepspeed=True)
@@ -224,21 +225,6 @@ def test_deepspeed_defaults(tmpdir):
     assert isinstance(plugin.config["zero_optimization"], dict)
 
 
-@RunIf(min_gpus=1, deepspeed=True)
-def test_invalid_deepspeed_defaults_no_precision(tmpdir):
-    """Test to ensure that using defaults, if precision is not set to 16, we throw an exception."""
-    model = BoringModel()
-    trainer = Trainer(
-        default_root_dir=tmpdir,
-        fast_dev_run=True,
-        plugins='deepspeed',
-    )
-    with pytest.raises(
-        MisconfigurationException, match='To use DeepSpeed ZeRO Optimization, you must set precision=16.'
-    ):
-        trainer.fit(model)
-
-
 @RunIf(min_gpus=1, deepspeed=True, special=True)
 def test_warn_deepspeed_override_backward(tmpdir):
     """Test to ensure that if the backward hook in the LightningModule is overridden, we throw a warning."""
@@ -448,6 +434,13 @@ def test_deepspeed_multigpu(tmpdir, deepspeed_config):
     _assert_save_model_is_equal(model, tmpdir, trainer)
 
 
+@RunIf(min_gpus=1, deepspeed=True, special=True)
+def test_deepspeed_fp32_works(tmpdir):
+    model = BoringModel()
+    trainer = Trainer(default_root_dir=tmpdir, gpus=1, plugins='deepspeed_stage_3', fast_dev_run=True)
+    trainer.fit(model)
+
+
 class ModelParallelClassificationModel(LightningModule):
 
     def __init__(self, lr: float = 0.01, num_blocks: int = 5):