diff --git a/docker-compose.yaml b/docker-compose.yaml
index ee137e83c..82b3c18b6 100644
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@@ -59,6 +59,7 @@ services:
     #           capabilities: [gpu, utility]
     #
     # For legacy NVIDIA driver (for older NVIDIA Container Toolkit):
+    # Request compute for CUDA libraries (libcuda.so.1) and utility for NVML.
     # environment:
     #   NVIDIA_DRIVER_CAPABILITIES: "compute,utility"
     # init: true
@@ -68,7 +69,7 @@ services:
     #       devices:
     #         - driver: nvidia
     #           count: 1
-    #           capabilities: [gpu, utility]
+    #           capabilities: [gpu, compute, utility]
 
   ## Uncomment for PostgreSQL-backed knowledge base (see Agents docs)
   # postgres:
diff --git a/docs/content/features/distributed-mode.md b/docs/content/features/distributed-mode.md
index a2aa758cc..7f1aa9340 100644
--- a/docs/content/features/distributed-mode.md
+++ b/docs/content/features/distributed-mode.md
@@ -417,8 +417,12 @@ usage is reported back to the frontend:
   NVML library (and therefore `nvidia-smi`) is not available inside the
   container. CUDA compute still works, but the worker cannot query free VRAM
   and the Nodes page will show the node as fully used. Set
-  `NVIDIA_DRIVER_CAPABILITIES=compute,utility` (or, with the NVIDIA CDI
-  runtime, list `capabilities: [gpu, utility]` on the device reservation).
+  `NVIDIA_DRIVER_CAPABILITIES=compute,utility` when using the NVIDIA runtime.
+  For Docker Compose with `driver: nvidia`, use
+  `capabilities: [gpu, compute, utility]` on the device reservation.
+  Docker derives driver capabilities from this reservation, so include `compute`
+  for CUDA libraries such as `libcuda.so.1`. The `utility` capability alone
+  enables monitoring but does not provide CUDA libraries.
 
 - **Run the container with `init: true` (or `docker run --init`).** The
   worker process becomes PID 1 in the container and cannot reap zombies on
diff --git a/docs/content/reference/nvidia-l4t.md b/docs/content/reference/nvidia-l4t.md
index 2adac3a84..e3b54020a 100644
--- a/docs/content/reference/nvidia-l4t.md
+++ b/docs/content/reference/nvidia-l4t.md
@@ -88,8 +88,10 @@ page in the frontend shows the node as fully used, check two things:
    NVML work inside the container. With `--gpus all` alone (or
    `--runtime nvidia` without extra flags) only `compute` is wired in on
    some driver versions. Add `-e NVIDIA_DRIVER_CAPABILITIES=compute,utility`
-   to your `docker run`, or `capabilities: [gpu, utility]` in compose /
-   Kubernetes device reservations.
+   to your `docker run`. For Docker Compose with `driver: nvidia`, use
+   `capabilities: [gpu, compute, utility]` on the device reservation.
+   Include `compute` for CUDA libraries such as `libcuda.so.1`; `utility`
+   alone only provides monitoring libraries and tools.
 2. Pass `--init` to `docker run` (or `init: true` in compose) so the
    container has a proper PID 1 reaper - otherwise short-lived child
    processes like `nvidia-smi` can intermittently fail with