diff --git a/.github/scripts/validate_binaries.sh b/.github/scripts/validate_binaries.sh
index 96e59fa90d..5f81459111 100755
--- a/.github/scripts/validate_binaries.sh
+++ b/.github/scripts/validate_binaries.sh
@@ -28,7 +28,7 @@ get_python_config() {
             CONDA_EXTRA_PARAM=" -c conda-forge/label/python_rc -c conda-forge"
             ;;
         # Note: 3.15 / 3.15t are intentionally absent here. They are provisioned
-        # via uv (CPython 3.15.0b1) in the interpreter-setup branch below and
+        # via uv (CPython 3.15.0b4) in the interpreter-setup branch below and
         # never reach the conda create path that reads CONDA_EXTRA_PARAM.
         *)
             PYTHON_V=${MATRIX_PYTHON_VERSION}
@@ -200,7 +200,19 @@ run_smoke_tests() {
 
     # For pip install also test with latest numpy
     if [[ ${MATRIX_PACKAGE_TYPE} == 'wheel' ]]; then
-        pip3 install numpy --upgrade --force-reinstall
+        # PyPI publishes no cp315/cp315t numpy wheels, so a plain
+        # `pip install numpy` falls back to building from source: slow on Linux
+        # and macOS, and a hard failure on Windows, where MSVC cannot find
+        # stdalign.h ("fatal error C1083") while compiling numpy's SIMD headers.
+        # Preview wheels for every platform, Windows included, are on the
+        # nightly index -- take those instead, and never a source build.
+        if [[ ${MATRIX_PYTHON_VERSION} == "3.15" || ${MATRIX_PYTHON_VERSION} == "3.15t" ]]; then
+            pip3 install --pre numpy --upgrade --force-reinstall \
+                --only-binary=:all: \
+                --index-url https://download.pytorch.org/whl/nightly
+        else
+            pip3 install numpy --upgrade --force-reinstall
+        fi
         ${PYTHON_RUN} ./smoke_test/smoke_test.py ${test_suffix} ${compile_check}
     fi
 
@@ -215,11 +227,23 @@ test_cuda_device() {
     fi
 }
 
-# Cleanup conda environment
+# Cleanup the environment created for this run.
+#
+# ENV_NAME is a conda env name on the conda path but a venv *directory* on the
+# uv path, so `conda env remove -n` would fail with EnvironmentLocationNotFound
+# and, under `set -e`, fail the whole job after the tests had already passed.
 cleanup_conda_env() {
     if [[ ${TARGET_OS} != linux* ]]; then
-        conda deactivate
-        conda env remove -n "${ENV_NAME}"
+        if [[ ${USING_UV_VENV} == 'yes' ]]; then
+            # `deactivate` is a function defined by the venv activate script.
+            if declare -F deactivate > /dev/null; then
+                deactivate
+            fi
+            rm -rf "${ENV_NAME}"
+        else
+            conda deactivate
+            conda env remove -n "${ENV_NAME}"
+        fi
     fi
 }
 
@@ -309,22 +333,34 @@ fi
 
 # Setup the Python environment.
 #
-# Python 3.15 is still pre-release. The cp315/cp315t wheels are built against
-# CPython 3.15.0b1 (see pytorch .ci/docker/common/install_cpython.sh), but
-# conda-forge only ships 3.15.0a8 -- the pre-release ABI differs, so installing
-# the wheel under the conda interpreter segfaults on "import torch". Provision
-# the matching 3.15.0b1 interpreter with uv (from python-build-standalone)
+# Python 3.15 is still pre-release, and conda-forge's default channel does not
+# carry it, so provision the interpreter with uv (from python-build-standalone)
 # instead of conda. A --seed venv provides pip so the rest of the flow (pip3
 # install, smoke tests) is unchanged.
+#
+# Pin b4, NOT b1: `import torch` segfaults under the 3.15.0b1 build. The crash is
+# pybind11 3.0.4's gil_scoped_acquire teardown in python_tracer::init(), reached
+# from torch._C._autograd_init():
+#     THPAutograd_initExtension -> python_tracer::init()
+#       -> ~gil_scoped_acquire() -> dec_ref() -> PyThreadState_Clear -> SIGSEGV
+# Verified with the cp315 nightly on both interpreters: b1 segfaults, b4 imports
+# and runs (matmul/autograd, and 3.15t with the GIL genuinely disabled).
+USING_UV_VENV="no"
 if [[ ${MATRIX_PYTHON_VERSION} == "3.15" || ${MATRIX_PYTHON_VERSION} == "3.15t" ]]; then
-    UV_PYTHON="3.15.0b1"
+    USING_UV_VENV="yes"
+    UV_PYTHON="3.15.0b4"
     if [[ ${MATRIX_PYTHON_VERSION} == "3.15t" ]]; then
-        UV_PYTHON="3.15.0b1+freethreaded"
+        UV_PYTHON="3.15.0b4+freethreaded"
     fi
     curl -LsSf https://astral.sh/uv/install.sh | sh
     source "${HOME}/.local/bin/env"
     uv venv --seed --python "${UV_PYTHON}" "${ENV_NAME}"
-    source "${ENV_NAME}/bin/activate"
+    # uv lays the venv out the platform way: Scripts/ on Windows, bin/ elsewhere.
+    if [[ ${TARGET_OS} == 'windows' ]]; then
+        source "${ENV_NAME}/Scripts/activate"
+    else
+        source "${ENV_NAME}/bin/activate"
+    fi
 else
     update_conda
     get_python_config
@@ -334,7 +370,11 @@ fi
 
 # Save original PATH for macos-arm64 workaround
 export OLD_PATH=${PATH}
-if [[ ${TARGET_OS} == 'macos-arm64' ]]; then
+# This promotes the *conda* env's bin to the front of PATH. On the uv path there
+# is no conda env to promote: CONDA_PREFIX still points at base (python 3.14),
+# so prepending it shadows the venv's python3/pip3 and the run would install and
+# validate the wrong interpreter instead of 3.15.
+if [[ ${TARGET_OS} == 'macos-arm64' && ${USING_UV_VENV} == 'no' ]]; then
     export PATH="${CONDA_PREFIX}/bin:${PATH}"
 fi