diff --git a/dfdx-core/Cargo.toml b/dfdx-core/Cargo.toml
index 7f4041fa..0eeac1f4 100644
--- a/dfdx-core/Cargo.toml
+++ b/dfdx-core/Cargo.toml
@@ -40,6 +40,7 @@ rayon = { version = "1.7.0", optional = true }
 libm = { workspace = true }
 wgpu = { version = "0.18.0", optional = true }
 futures-lite = { version = "2.0.1", optional = true }
+thingbuf = { version = "0.1.4", optional = true }
 
 [dev-dependencies]
 tempfile = "3.3.0"
@@ -61,7 +62,7 @@ fast-alloc = ["std"]
 
 cuda = ["dep:cudarc", "dep:glob"]
 cudnn = ["cuda", "cudarc?/cudnn"]
-webgpu = ["dep:wgpu", "dep:futures-lite", "wgpu/expose-ids"]
+webgpu = ["dep:wgpu", "dep:futures-lite", "dep:thingbuf", "wgpu/expose-ids"]
 
 f16 = ["dep:half", "cudarc?/f16", "gemm?/f16"]
 
diff --git a/dfdx-core/src/tensor/webgpu/allocate.rs b/dfdx-core/src/tensor/webgpu/allocate.rs
index 52b22724..49162381 100644
--- a/dfdx-core/src/tensor/webgpu/allocate.rs
+++ b/dfdx-core/src/tensor/webgpu/allocate.rs
@@ -74,7 +74,7 @@ impl<E: Unit + SafeZeros> ZeroFillStorage<E> for Webgpu {
 impl<E: Unit> OnesTensor<E> for Webgpu {
     fn try_ones_like<S: HasShape>(&self, src: &S) -> Result<Tensor<S::Shape, E, Self>, Error> {
         let shape = *src.shape();
-        let buf = std::vec![E::ONE; shape.num_elements()];
+        let buf = vec![E::ONE; shape.num_elements()];
         self.tensor_from_host_buf(shape, buf)
     }
 }
@@ -90,7 +90,7 @@ where
         diagonal: impl Into<Option<isize>>,
     ) -> Result<Tensor<S::Shape, E, Self>, Error> {
         let shape = *src.shape();
-        let mut data = std::vec![val; shape.num_elements()];
+        let mut data = vec![val; shape.num_elements()];
         let offset = diagonal.into().unwrap_or(0);
         triangle_mask(&mut data, &shape, true, offset);
         self.tensor_from_host_buf(shape, data)
@@ -103,7 +103,7 @@ where
         diagonal: impl Into<Option<isize>>,
     ) -> Result<Tensor<S::Shape, E, Self>, Error> {
         let shape = *src.shape();
-        let mut data = std::vec![val; shape.num_elements()];
+        let mut data = vec![val; shape.num_elements()];
         let offset = diagonal.into().unwrap_or(0);
         triangle_mask(&mut data, &shape, false, offset);
         self.tensor_from_host_buf(shape, data)
@@ -113,7 +113,7 @@ where
 impl<E: Unit> OneFillStorage<E> for Webgpu {
     fn try_fill_with_ones(&self, storage: &mut Self::Vec) -> Result<(), Error> {
         let len = storage.size() as usize / std::mem::size_of::<E>();
-        let buf = std::vec![E::ONE; len];
+        let buf = vec![E::ONE; len];
         storage
             .data
             .copy_to_device::<E>(&self.dev, &self.queue, &buf);
diff --git a/dfdx-core/src/tensor/webgpu/device.rs b/dfdx-core/src/tensor/webgpu/device.rs
index a82e7019..3cba06c7 100644
--- a/dfdx-core/src/tensor/webgpu/device.rs
+++ b/dfdx-core/src/tensor/webgpu/device.rs
@@ -11,6 +11,12 @@ use crate::{
     },
 };
 
+#[cfg(feature = "no-std")]
+use spin::Mutex;
+
+#[cfg(not(feature = "no-std"))]
+use std::sync::Mutex;
+
 use std::{marker::PhantomData, sync::Arc, vec::Vec};
 
 use super::allocate::round_to_buffer_alignment;
@@ -52,7 +58,7 @@ impl Buffer {
     }
 
     pub(crate) fn copy_to_host<E: Unit>(&self, dev: &Device, queue: &Queue, buf: &mut [E]) {
-        let (sender, receiver) = std::sync::mpsc::channel();
+        let (sender, receiver) = thingbuf::mpsc::channel(1);
         let buffer = dev.create_buffer(&BufferDescriptor {
             label: None,
             size: self.size() as u64,
@@ -66,11 +72,11 @@ impl Buffer {
         }
         let slice = buffer.slice(..self.size() as u64);
         slice.map_async(wgpu::MapMode::Read, move |_| {
-            sender.send(()).unwrap();
+            futures_lite::future::block_on(sender.send(())).unwrap();
         });
         dev.poll(Maintain::Wait);
 
-        let _ = receiver.recv().unwrap();
+        let _ = futures_lite::future::block_on(receiver.recv());
         let data = slice.get_mapped_range();
         // TODO: How are we sure this is safe?
         let slice = unsafe {
@@ -110,7 +116,7 @@ impl Default for Webgpu {
     }
 }
 
-static CONSTRUCTOR_MUTEX: std::sync::Mutex<()> = std::sync::Mutex::new(());
+static CONSTRUCTOR_MUTEX: Mutex<()> = Mutex::new(());
 
 impl Webgpu {
     pub fn seed_from_u64(seed: u64) -> Self {
@@ -118,7 +124,11 @@ impl Webgpu {
     }
 
     pub fn try_build(seed: u64) -> Result<Self, Error> {
-        let _lock = CONSTRUCTOR_MUTEX.lock().unwrap();
+        #[cfg(feature = "no-std")]
+        let _lock = { CONSTRUCTOR_MUTEX.lock() };
+        #[cfg(not(feature = "no-std"))]
+        let _lock = { CONSTRUCTOR_MUTEX.lock().unwrap() };
+
         let cpu = Cpu::seed_from_u64(seed);
         let instance = Arc::new(Instance::new(InstanceDescriptor::default()));
         let adapter = futures_lite::future::block_on(instance.request_adapter(&Default::default()))
@@ -332,7 +342,7 @@ impl<E: Unit> Storage<E> for Webgpu {
             device: self.cpu.clone(),
             tape: NoneTape,
         };
-        let buf = std::sync::Arc::get_mut(&mut cpu_tensor.data).unwrap();
+        let buf = Arc::get_mut(&mut cpu_tensor.data).unwrap();
         tensor.data.copy_to_host::<E>(&self.dev, &self.queue, buf);
         self.cpu.tensor_to_vec::<S, _>(&cpu_tensor)
     }
diff --git a/dfdx-core/src/tensor_ops/stack/webgpu_kernel.rs b/dfdx-core/src/tensor_ops/stack/webgpu_kernel.rs
index d2aebfc8..113aae1a 100644
--- a/dfdx-core/src/tensor_ops/stack/webgpu_kernel.rs
+++ b/dfdx-core/src/tensor_ops/stack/webgpu_kernel.rs
@@ -1,4 +1,5 @@
 use crate::{shapes::*, tensor::Webgpu};
+use std::vec::Vec;
 
 impl<E: Dtype> super::StackKernel<E> for Webgpu {
     fn forward<S: Shape, Num: Dim>(