diff --git a/scripts/build.sh b/scripts/build.sh
index 8845f3b..90539e2 100755
--- a/scripts/build.sh
+++ b/scripts/build.sh
@@ -4,14 +4,16 @@
 #   sdk       venv + AMD's ROCm SDK wheels for $PRAIN_GPU_ARCH
 #   fetch     clone PyTorch and vLLM into build/
 #   torch     PyTorch from source -> build/wheels, installed into the venv
+#   torchvision  torchvision from source -> build/wheels, installed into the venv
 #   vllm      vLLM from source (adds $PRAIN_GPU_ARCH to its HIP arch list), installed editable
 #   prain     this package, installed editable, and its test suite
-# usage: scripts/build.sh STEP...      Versions: PRAIN_ROCM_VERSION, PRAIN_TORCH_REF, PRAIN_VLLM_REF
+# usage: scripts/build.sh STEP...   Versions: PRAIN_ROCM_VERSION, PRAIN_TORCH_REF, PRAIN_VISION_REF, PRAIN_VLLM_REF
 set -euo pipefail
 cd "$(dirname "$0")/.."
 ROCM_INDEX=${PRAIN_ROCM_INDEX:-https://stable.repo.amd.com/rocm/whl-next/}
 ROCM_VERSION=${PRAIN_ROCM_VERSION:-10.1.0}
 TORCH_REF=${PRAIN_TORCH_REF:-v2.13.0}
+VISION_REF=${PRAIN_VISION_REF:-v0.28.0}
 VLLM_REF=${PRAIN_VLLM_REF:-v0.32.0}
 PYTHON=${PRAIN_PYTHON:-python3.13}
 
@@ -90,6 +92,16 @@ torch() {
     env -u LD_LIBRARY_PATH python -c 'import torch; x = torch.ones(4, device="cuda"); print(torch.__version__, torch.version.hip, torch.cuda.get_device_properties(0).gcnArchName, (x * 2).sum().item(), torch.backends.openmp.is_available(), torch.get_num_threads())'
 }
 
+# transformers' Gemma 4 processor imports torchvision, even for text-only serving.
+torchvision() {
+    [ -d build/vision/.git ] || git clone --depth 1 --branch "$VISION_REF" \
+        https://github.com/pytorch/vision build/vision
+    (cd build/vision && env FORCE_CUDA=1 PYTORCH_ROCM_ARCH="$PRAIN_GPU_ARCH" MAX_JOBS="$PRAIN_JOBS" \
+        nice -n 19 python -m pip wheel --no-build-isolation --no-deps -v -w "$PRAIN_ROOT/build/wheels" .)
+    python -m pip install --no-deps --force-reinstall build/wheels/torchvision-*.whl
+    env -u LD_LIBRARY_PATH python -c 'import torch, torchvision; print(torchvision.__version__, torch.ops.torchvision.nms(torch.rand(4, 4, device="cuda"), torch.rand(4, device="cuda"), 0.5).device)'
+}
+
 vllm() {
     local src=build/vllm site
     site=$(python -c 'import sysconfig; print(sysconfig.get_paths()["purelib"])')