diff --git a/k8s/apps/llm-serving/kustomization.yaml b/k8s/apps/llm-serving/kustomization.yaml
index 4d09759..31d77a3 100644
--- a/k8s/apps/llm-serving/kustomization.yaml
+++ b/k8s/apps/llm-serving/kustomization.yaml
@@ -10,7 +10,22 @@ kind: Kustomization
 # way after any edit here: a GPU predictor restart is a weights reload measured
 # in tens of seconds, not a rolling update.
 resources:
-  - clef-flash.yaml
+  # clef-flash.yaml is NOT listed: the model cannot run on this cluster.
+  #
+  # Clef needs SGLang v0.5.22 or newer, and SGLang publishes that only on CUDA 13
+  # (the last CUDA 12 tag is v0.5.19-cu129, which predates Clef support). CUDA 13
+  # dropped Volta kernels, and every GPU here is a Tesla V100 (sm_70):
+  #
+  #   torch.AcceleratorError: CUDA error: no kernel image is available for
+  #   execution on the device
+  #
+  # SGLang also states sm75 as its floor: the README hardware list omits V100,
+  # sm75 support was removed in sgl-project/sglang#9207, and FlashInfer needs
+  # sm75+. So no SGLang build exists that has both Clef and Volta kernels, and
+  # no flag or dtype change bridges that gap.
+  #
+  # Re-add it when the model gets an Ampere-or-newer GPU. The manifest itself is
+  # kept in git (k8s/apps/llm-serving/clef-flash.yaml) with the same reasoning.
   # ornith and reasoning are live but unmanaged: their manifests were never committed
   # to this directory, so listing them made `kustomize build` fail and left the whole
   # Application in ComparisonError. Remove the entries rather than the models. The