diff --git a/.github/unittest/linux_libs/scripts_brax/environment.yml b/.github/unittest/linux_libs/scripts_brax/environment.yml
index 695278f3adb..63e26428d55 100644
--- a/.github/unittest/linux_libs/scripts_brax/environment.yml
+++ b/.github/unittest/linux_libs/scripts_brax/environment.yml
@@ -19,6 +19,6 @@ dependencies:
     - pyyaml
     - scipy
     - hydra-core
-    - jax[cuda12]
+    - jax[cuda12]>=0.7.0
     - brax
     - psutil
diff --git a/.github/unittest/linux_libs/scripts_minari/environment.yml b/.github/unittest/linux_libs/scripts_minari/environment.yml
index e1362721b12..9c310d805f5 100644
--- a/.github/unittest/linux_libs/scripts_minari/environment.yml
+++ b/.github/unittest/linux_libs/scripts_minari/environment.yml
@@ -24,7 +24,7 @@ dependencies:
     - ale-py
     - gymnasium-robotics
     - minari[create]
-    - jax
+    - jax>=0.7.0
     - mujoco               
     - mujoco-py<2.2,>=2.1
     - minigrid
diff --git a/pyproject.toml b/pyproject.toml
index 9a6014d269d..ca7d962d7de 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -75,6 +75,7 @@ offline-data = [
 ]
 marl = ["vmas>=1.2.10", "pettingzoo>=1.24.1", "dm-meltingpot"]
 open_spiel = ["open_spiel>=1.5"]
+brax = ["jax[cuda12]>=0.7.0", "brax"]
 llm = [
     "transformers",
     "vllm",
diff --git a/torchrl/envs/libs/jax_utils.py b/torchrl/envs/libs/jax_utils.py
index 337e9e9a1a9..935b87460de 100644
--- a/torchrl/envs/libs/jax_utils.py
+++ b/torchrl/envs/libs/jax_utils.py
@@ -42,13 +42,13 @@ def _tree_flatten(x, batch_size: torch.Size):
 
 
 def _ndarray_to_tensor(value: jnp.ndarray | np.ndarray) -> torch.Tensor:  # noqa: F821
-    from jax import dlpack as jax_dlpack, numpy as jnp
+    from jax import numpy as jnp
 
     # JAX arrays generated by jax.vmap would have Numpy dtypes.
     if value.dtype in _dtype_conversion:
         value = value.view(_dtype_conversion[value.dtype])
     if isinstance(value, jnp.ndarray):
-        dlpack_tensor = jax_dlpack.to_dlpack(value)
+        dlpack_tensor = value.__dlpack__()
     elif isinstance(value, np.ndarray):
         dlpack_tensor = value.__dlpack__()
     else:
@@ -61,7 +61,9 @@ def _ndarray_to_tensor(value: jnp.ndarray | np.ndarray) -> torch.Tensor:  # noqa
 def _tensor_to_ndarray(value: torch.Tensor) -> jnp.ndarray:  # noqa: F821
     from jax import dlpack as jax_dlpack
 
-    return jax_dlpack.from_dlpack(torch_dlpack.to_dlpack(value.contiguous()))
+    # Detach the tensor to remove gradients before converting to DLPack
+    value = value.contiguous().detach()
+    return jax_dlpack.from_dlpack(value)
 
 
 def _get_object_fields(obj) -> dict: