diff --git a/examples/compute_workgroups.py b/examples/compute_workgroups.py
new file mode 100644
index 00000000..16ec58c9
--- /dev/null
+++ b/examples/compute_workgroups.py
@@ -0,0 +1,116 @@
+"""
+A simple compute example demonstrating GPU workgroups and invocation IDs.
+
+Each thread writes its global, local, and workgroup IDs into a storage buffer
+so the relationship between them can be inspected.
+"""
+
+import numpy as np
+import wgpu
+
+# define workgroup configuration
+
+workgroup_size = 4
+workgroups = 3
+total_threads = workgroup_size * workgroups
+
+# Each thread writes 3 uint32 values
+output_elements = total_threads * 3
+output_bytes = output_elements * 4
+
+# compute shader
+
+shader_source = f"""
+@group(0) @binding(0)
+var<storage, read_write> out: array<u32>;
+
+@compute
+@workgroup_size({workgroup_size}, 1, 1)
+fn main(
+    @builtin(global_invocation_id) global_id : vec3<u32>,
+    @builtin(local_invocation_id)  local_id  : vec3<u32>,
+    @builtin(workgroup_id)         wg_id     : vec3<u32>,
+) {{
+    let base: u32 = global_id.x * 3u;
+
+    out[base]     = global_id.x;
+    out[base + 1] = local_id.x;
+    out[base + 2] = wg_id.x;
+}}
+"""
+
+# adapter and device
+
+adapter = wgpu.gpu.request_adapter_sync(power_preference="high-performance")
+device = adapter.request_device_sync()
+
+# storage buffer
+
+output_buffer = device.create_buffer(
+    size=output_bytes,
+    usage=wgpu.BufferUsage.STORAGE | wgpu.BufferUsage.COPY_SRC,
+)
+
+# Shader module and compute pipeline
+
+shader_module = device.create_shader_module(code=shader_source)
+
+compute_pipeline = device.create_compute_pipeline(
+    layout="auto",
+    compute={"module": shader_module, "entry_point": "main"},
+)
+
+# bind group
+
+bind_group = device.create_bind_group(
+    layout=compute_pipeline.get_bind_group_layout(0),
+    entries=[
+        {
+            "binding": 0,
+            "resource": {
+                "buffer": output_buffer,
+                "offset": 0,
+                "size": output_buffer.size,
+            },
+        }
+    ],
+)
+
+# encode, dispatch and submit
+
+command_encoder = device.create_command_encoder()
+compute_pass = command_encoder.begin_compute_pass()
+
+compute_pass.set_pipeline(compute_pipeline)
+compute_pass.set_bind_group(0, bind_group)
+compute_pass.dispatch_workgroups(workgroups, 1, 1)
+
+compute_pass.end()
+
+device.queue.submit([command_encoder.finish()])
+
+# results
+
+raw = device.queue.read_buffer(output_buffer)
+values = np.frombuffer(raw, dtype=np.uint32)
+
+print(
+    f"Dispatched {workgroups} workgroup(s) of {workgroup_size} thread(s) each "
+    f"({total_threads} threads total).\n"
+)
+
+print(f"{'Thread':>6}  {'global_id':>9}  {'local_id':>8}  {'workgroup_id':>12} ")
+
+for i in range(total_threads):
+    global_id = values[i * 3]
+    local_id = values[i * 3 + 1]
+    workgroup_id = values[i * 3 + 2]
+
+    print(f"{i:>6}  {global_id:>9}  {local_id:>8}  {workgroup_id:>12}")
+
+    # verify invocation ID relationships
+    assert global_id == i
+    assert local_id == i % workgroup_size
+    assert workgroup_id == i // workgroup_size
+
+print("Invocation ID mapping verified")