diff --git a/torchrl/envs/libs/brax.py b/torchrl/envs/libs/brax.py
index c86ba9a543c..ac4cd71ddad 100644
--- a/torchrl/envs/libs/brax.py
+++ b/torchrl/envs/libs/brax.py
@@ -80,8 +80,10 @@ class BraxWrapper(_EnvWrapper):
     Examples:
         >>> import brax.envs
         >>> from torchrl.envs import BraxWrapper
+        >>> import torch
+        >>> device = "cuda" if torch.cuda.is_available() else "cpu"
         >>> base_env = brax.envs.get_environment("ant")
-        >>> env = BraxWrapper(base_env)
+        >>> env = BraxWrapper(base_env, device=device)
         >>> env.set_seed(0)
         >>> td = env.reset()
         >>> td["action"] = env.action_spec.rand()
@@ -111,7 +113,9 @@ class BraxWrapper(_EnvWrapper):
     and report the execution time for a short rollout:
 
     Examples:
+        >>> import torch
         >>> from torch.utils.benchmark import Timer
+        >>> device = "cuda" if torch.cuda.is_available() else "cpu"
         >>> for batch_size in [4, 16, 128]:
         ...     timer = Timer('''
         ... env.rollout(100)
@@ -119,7 +123,7 @@ class BraxWrapper(_EnvWrapper):
         ...     setup=f'''
         ... import brax.envs
         ... from torchrl.envs import BraxWrapper
-        ... env = BraxWrapper(brax.envs.get_environment("ant"), batch_size=[{batch_size}])
+        ... env = BraxWrapper(brax.envs.get_environment("ant"), batch_size=[{batch_size}], device="{device}")
         ... env.set_seed(0)
         ... env.rollout(2)
         ... ''')
@@ -459,7 +463,9 @@ class BraxEnv(BraxWrapper):
 
     Examples:
         >>> from torchrl.envs import BraxEnv
-        >>> env = BraxEnv("ant")
+        >>> import torch
+        >>> device = "cuda" if torch.cuda.is_available() else "cpu"
+        >>> env = BraxEnv("ant", device=device)
         >>> env.set_seed(0)
         >>> td = env.reset()
         >>> td["action"] = env.action_spec.rand()
@@ -489,13 +495,16 @@ class BraxEnv(BraxWrapper):
     and report the execution time for a short rollout:
 
     Examples:
+        >>> import torch
+        >>> from torch.utils.benchmark import Timer
+        >>> device = "cuda" if torch.cuda.is_available() else "cpu"
         >>> for batch_size in [4, 16, 128]:
         ...     timer = Timer('''
         ... env.rollout(100)
         ... ''',
         ...     setup=f'''
         ... from torchrl.envs import BraxEnv
-        ... env = BraxEnv("ant", batch_size=[{batch_size}])
+        ... env = BraxEnv("ant", batch_size=[{batch_size}], device="{device}")
         ... env.set_seed(0)
         ... env.rollout(2)
         ... ''')