diff --git a/stable_baselines3/common/buffers.py b/stable_baselines3/common/buffers.py
index 004adae90..d0eb0856c 100644
--- a/stable_baselines3/common/buffers.py
+++ b/stable_baselines3/common/buffers.py
@@ -136,6 +136,8 @@ def to_torch(self, array: np.ndarray, copy: bool = True) -> th.Tensor:
         :return:
         """
         if copy:
+            if hasattr(th, "backends") and th.backends.mps.is_built():
+                return th.tensor(array, dtype=th.float32, device=self.device)
             return th.tensor(array, device=self.device)
         return th.as_tensor(array, device=self.device)
 
diff --git a/stable_baselines3/common/envs/bit_flipping_env.py b/stable_baselines3/common/envs/bit_flipping_env.py
index 4d99313ea..d0d48df0c 100644
--- a/stable_baselines3/common/envs/bit_flipping_env.py
+++ b/stable_baselines3/common/envs/bit_flipping_env.py
@@ -81,7 +81,7 @@ def convert_if_needed(self, state: np.ndarray) -> Union[int, np.ndarray]:
             state = state.astype(np.int32)
             # The internal state is the binary representation of the
             # observed one
-            return int(sum(state[i] * 2**i for i in range(len(state))))
+            return int(sum(int(state[i]) * 2**i for i in range(len(state))))
 
         if self.image_obs_space:
             size = np.prod(self.image_shape)
diff --git a/stable_baselines3/common/utils.py b/stable_baselines3/common/utils.py
index a5a5476b9..562ff132a 100644
--- a/stable_baselines3/common/utils.py
+++ b/stable_baselines3/common/utils.py
@@ -486,6 +486,8 @@ def obs_as_tensor(obs: Union[np.ndarray, dict[str, np.ndarray]], device: th.devi
     if isinstance(obs, np.ndarray):
         return th.as_tensor(obs, device=device)
     elif isinstance(obs, dict):
+        if hasattr(th, "backends") and th.backends.mps.is_built():
+            return {key: th.as_tensor(_obs, dtype=th.float32, device=device) for (key, _obs) in obs.items()}
         return {key: th.as_tensor(_obs, device=device) for (key, _obs) in obs.items()}
     else:
         raise Exception(f"Unrecognized type of observation {type(obs)}")
@@ -526,6 +528,7 @@ def get_available_accelerator() -> str:
     """
     if hasattr(th, "backends") and th.backends.mps.is_built():
         # MacOS Metal GPU
+        th.set_default_dtype(th.float32)
         return "mps"
     elif th.cuda.is_available():
         return "cuda"
diff --git a/tests/test_spaces.py b/tests/test_spaces.py
index cd38e1ecd..102c0ef8f 100644
--- a/tests/test_spaces.py
+++ b/tests/test_spaces.py
@@ -4,6 +4,7 @@
 import gymnasium as gym
 import numpy as np
 import pytest
+import torch as th
 from gymnasium import spaces
 from gymnasium.spaces.space import Space
 
@@ -151,6 +152,8 @@ def test_discrete_obs_space(model_class, env):
     ],
 )
 def test_float64_action_space(model_class, obs_space, action_space):
+    if hasattr(th, "backends") and th.backends.mps.is_built():
+        pytest.skip("MPS framework doesn't support float64")
     env = DummyEnv(obs_space, action_space)
     env = gym.wrappers.TimeLimit(env, max_episode_steps=200)
     if isinstance(env.observation_space, spaces.Dict):