diff --git a/crates/cubecl-common/Cargo.toml b/crates/cubecl-common/Cargo.toml
index 902431cd0..30302b243 100644
--- a/crates/cubecl-common/Cargo.toml
+++ b/crates/cubecl-common/Cargo.toml
@@ -12,7 +12,7 @@ version.workspace = true
 
 [features]
 default = ["std"]
-std = ["rand/std"]
+std = ["rand/std", "pollster"]
 
 [target.'cfg(target_family = "wasm")'.dependencies]
 getrandom = { workspace = true, features = ["js"] }
@@ -24,7 +24,7 @@ spin = { workspace = true }                      # using in place of use std::sy
 derive-new = { workspace = true }
 serde = { workspace = true }
 rand = { workspace = true }
-pollster = { workspace = true }
+pollster = { workspace = true, optional = true }
 
 [dev-dependencies]
 dashmap = { workspace = true }
diff --git a/crates/cubecl-linalg/src/tensor/contiguous.rs b/crates/cubecl-linalg/src/tensor/contiguous.rs
index 87e344395..c040b89bf 100644
--- a/crates/cubecl-linalg/src/tensor/contiguous.rs
+++ b/crates/cubecl-linalg/src/tensor/contiguous.rs
@@ -62,7 +62,7 @@ pub fn into_contiguous<R: Runtime, E: CubePrimitive>(
     // Vectorization is only enabled when the last dimension is contiguous.
     let rank = input.strides.len();
     let vectorization_factor =
-        tensor_vectorization_factor(&[4, 2], &input.shape, &input.strides, rank - 1);
+        tensor_vectorization_factor(&[4, 2], input.shape, input.strides, rank - 1);
 
     let num_elems: usize = input.shape.iter().product();
     let cube_count = calculate_cube_count_elemwise(
@@ -73,14 +73,14 @@ pub fn into_contiguous<R: Runtime, E: CubePrimitive>(
     let output = TensorHandle::new_contiguous(input.shape.to_vec(), handle);
 
     into_contiguous_kernel::launch::<E, R>(
-        &client,
+        client,
         cube_count,
         CubeDim::default(),
         TensorArg::vectorized(
             vectorization_factor,
-            &input.handle,
-            &input.strides,
-            &input.shape,
+            input.handle,
+            input.strides,
+            input.shape,
         ),
         TensorArg::vectorized(
             vectorization_factor,