@@ -7,13 +7,15 @@ export HF_HUB_DISABLE_XET=1
 # Arguments:
 # 1. model_id: The Hugging Face repository ID (e.g., "organization/model_name")
 # 2. subdir: The optional subdirectory in the repo to look for files (pass "" if not used)
-# 3. file_names: A space-separated list of filenames to be downloaded
+# 3. revision: The commit hash to download
+# 4. file_names: A space-separated list of filenames to be downloaded
 # Returns:
 # The directory containing the downloaded files
 function download_hf_files() {
   local model_id="$1"
   local subdir="$2"
-  shift 2
+  local revision="$3"
+  shift 3
   local file_names=("$@")  # Capture all remaining arguments as an array
 
   local download_dir
@@ -24,7 +26,8 @@ from huggingface_hub import hf_hub_download
 # Download the first file and get its directory
 path = hf_hub_download(
     repo_id='${model_id}',
-    filename='${subdir:+${subdir}/}${file_names[0]}'
+    filename='${subdir:+${subdir}/}${file_names[0]}',
+    revision='${revision}'
 )
 import os
 print(os.path.dirname(path))")
@@ -41,7 +44,8 @@ from huggingface_hub import hf_hub_download
 # Download the file
 hf_hub_download(
     repo_id='${model_id}',
-    filename='${subdir:+${subdir}/}${file_name}'
+    filename='${subdir:+${subdir}/}${file_name}',
+    revision='${revision}'
 )"
 
     if [ $? -ne 0 ]; then
@@ -67,6 +71,10 @@ if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
         SUBDIR="$2"
         shift 2
         ;;
+      --revision)
+        REVISION="$2"
+        shift 2
+        ;;
       --files)
         shift
         FILES_TO_DOWNLOAD=()
@@ -83,13 +91,13 @@ if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
   done
 
   # Validate required arguments
-  if [ -z "$MODEL_ID" ] || [ ${#FILES_TO_DOWNLOAD[@]} -eq 0 ]; then
-    echo "Usage: $0 --model_id <model_id> --subdir <subdir> --files <file1> [<file2> ...]" >&2
+  if [ -z "$MODEL_ID" ] || [ -z "$REVISION" ] || [ ${#FILES_TO_DOWNLOAD[@]} -eq 0 ]; then
+    echo "Usage: $0 --model_id <model_id> --revision <commit> --subdir <subdir> --files <file1> [<file2> ...]" >&2
     exit 1
   fi
 
   # Call the function
-  DOWNLOAD_DIR=$(download_hf_files "$MODEL_ID" "$SUBDIR" "${FILES_TO_DOWNLOAD[@]}")
+  DOWNLOAD_DIR=$(download_hf_files "$MODEL_ID" "$SUBDIR" "$REVISION" "${FILES_TO_DOWNLOAD[@]}")
   if [ $? -eq 0 ]; then
     echo "$DOWNLOAD_DIR"
   else
 
@@ -21,6 +21,7 @@ build_dir=$(cd "${build_dir}" && pwd)
 cd "${et_root}"
 
 collect_artifacts() {
+    local file operator_dir artifact_dir
     if [[ -n "${RUNNER_ARTIFACT_DIR:-}" ]]; then
         mkdir -p "${RUNNER_ARTIFACT_DIR}/esp32s3"
         for file in "${build_dir}"/*.log "${build_dir}"/*.bpte \
@@ -35,6 +36,18 @@ collect_artifacts() {
                 cp "${file}" "${RUNNER_ARTIFACT_DIR}/esp32s3/"
             fi
         done
+        for operator_dir in "${build_dir}"/operator-library-*; do
+            [[ -d "${operator_dir}" ]] || continue
+            artifact_dir="${RUNNER_ARTIFACT_DIR}/esp32s3/${operator_dir##*/}"
+            mkdir -p "${artifact_dir}"
+            for file in "${operator_dir}"/*.log "${operator_dir}"/*.bpte \
+                "${operator_dir}/sdkconfig" "${operator_dir}"/*.elf \
+                "${operator_dir}/merged-binary.bin"; do
+                if [[ -f "${file}" ]]; then
+                    cp "${file}" "${artifact_dir}/"
+                fi
+            done
+        done
     fi
 }
 trap collect_artifacts EXIT
@@ -54,6 +67,9 @@ python examples/espressif/export_espnn_test_programs.py \
 # runs inline without pthreadpool, which needs POSIX calls ESP-IDF lacks.
 espnn_ops=$(tr -d '\n' < "${build_dir}/espnn-tests/operators.txt" \
     | tr ',' '\n' | grep -v '^quantized_decomposed::' | paste -sd, -)
+if [[ "${espnn_kernels}" == optimized ]]; then
+    espnn_ops="${espnn_ops},aten::sin.out"
+fi
 
 cmake --preset esp-baremetal -G Ninja -B "${build_dir}/runtime" \
     -DCMAKE_TOOLCHAIN_FILE="${IDF_PATH}/tools/cmake/toolchain-esp32s3.cmake" \
@@ -136,3 +152,16 @@ import json, sys
 for entry in json.load(open(sys.argv[1])):
     print(entry["name"], entry["atol"], entry["rtol"])
 ' "${build_dir}/espnn-tests/manifest.json")
+
+if [[ "${espnn_kernels}" == optimized ]]; then
+    # Stop on failure so later cases cannot overwrite its firmware and logs.
+    ESPRESSIF_BUILD_DIR="${build_dir}" python -m pytest \
+        -x -v --tb=short backends/espressif/test/ops -k implementation \
+        2>&1 | tee "${build_dir}/operator-library-tests.log"
+    for sdkconfig in "${build_dir}"/operator-library-*/sdkconfig; do
+        if ! grep -qx 'CONFIG_NN_OPTIMIZED=y' "${sdkconfig}"; then
+            echo "Expected CONFIG_NN_OPTIMIZED=y in ${sdkconfig}" >&2
+            exit 1
+        fi
+    done
+fi
@@ -0,0 +1,76 @@
+#!/usr/bin/env bash
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# Generates the ExecuTorch ESP-IDF component with every shipped profile,
+# builds the idf_component_smoke consumer for ESP32-S3 against each, and runs
+# the smoke profile build on the emulator.
+
+set -euo pipefail
+
+et_root=$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)
+build_dir="${ESPRESSIF_BUILD_DIR:-${et_root}/cmake-out-esp-idf-component}"
+export ESPRESSIF_TOOLS_DIR="${ESPRESSIF_TOOLS_DIR:-${RUNNER_TEMP:-/tmp}/executorch-espressif}"
+mkdir -p "${build_dir}"
+build_dir=$(cd "${build_dir}" && pwd)
+cd "${et_root}"
+
+collect_artifacts() {
+    if [[ -n "${RUNNER_ARTIFACT_DIR:-}" ]]; then
+        mkdir -p "${RUNNER_ARTIFACT_DIR}/esp-idf-component"
+        for file in "${build_dir}"/*.log "${build_dir}/components/executorch/VERSION"; do
+            if [[ -f "${file}" ]]; then
+                cp "${file}" "${RUNNER_ARTIFACT_DIR}/esp-idf-component/"
+            fi
+        done
+    fi
+}
+trap collect_artifacts EXIT
+
+bash examples/espressif/setup.sh --minimal 2>&1 | tee "${build_dir}/setup.log"
+# shellcheck source=/dev/null
+source "${ESPRESSIF_TOOLS_DIR}/setup_path.sh"
+
+python examples/espressif/export_smoke_model.py \
+    --output "${build_dir}/smoke.bpte" --pte-output "${build_dir}/smoke.pte" \
+    2>&1 | tee "${build_dir}/export.log"
+
+component_dir="${build_dir}/components/executorch"
+profiles=$(find examples/espressif/idf_profiles -name '*.ops' -exec basename {} .ops \; \
+    | sort | paste -sd, -)
+bash examples/espressif/build_idf_component.sh --profiles "${profiles}" \
+    --out "${component_dir}" 2>&1 | tee "${build_dir}/generate.log"
+
+project=examples/espressif/idf_component_smoke
+for profile in ${profiles//,/ }; do
+    profile_upper=$(echo "${profile}" | tr '[:lower:]-' '[:upper:]_')
+    firmware_dir="${build_dir}/firmware-${profile}"
+    printf 'CONFIG_ET_OP_PROFILE_%s=y\n' "${profile_upper}" \
+        > "${build_dir}/${profile}.defaults"
+    idf.py -C "${project}" -B "${firmware_dir}" \
+        -DIDF_TARGET=esp32s3 \
+        -DSDKCONFIG="${build_dir}/sdkconfig-${profile}" \
+        "-DSDKCONFIG_DEFAULTS=sdkconfig.defaults;${build_dir}/${profile}.defaults" \
+        -DET_COMPONENT_DIR="${component_dir}" \
+        -DET_SMOKE_PTE="${build_dir}/smoke.pte" build \
+        2>&1 | tee "${build_dir}/firmware-${profile}.log"
+done
+
+firmware_dir="${build_dir}/firmware-smoke"
+idf.py -C "${project}" -B "${firmware_dir}" merge-bin \
+    2>&1 | tee "${build_dir}/firmware-merge.log"
+timeout 130s esp-emu --chip esp32s3 \
+    --firmware "${firmware_dir}/merged-binary.bin" \
+    --elf "${firmware_dir}/et_component_smoke.elf" \
+    --net user --timeout 120s --exit-on 'Program complete.' \
+    2>&1 | tee "${build_dir}/emulator.log"
+for marker in "ET_COMPONENT_SMOKE: PASS" "Program complete."; do
+    if ! grep -qF "${marker}" "${build_dir}/emulator.log"; then
+        echo "FAIL: missing '${marker}'; see ${build_dir}/emulator.log" >&2
+        exit 1
+    fi
+done
+echo "PASS: generated ESP-IDF component ran the smoke model on the ESP32-S3 emulator."
@@ -57,26 +57,43 @@ PY
 }
 
 # Hosting lora adapter in personal repo for now.
+# The Hugging Face downloads below are pinned to commits the read-only
+# CI cache holds. To bump a pin, seed the cache first from a pytorch/executorch
+# branch (forks cannot write the cache): run pull.yml on it with
+# workflow_dispatch, or push to it after its pull request has the
+# ci-refresh-hf-cache label.
 python -m pip install -q huggingface_hub
 HF_ADAPTER_REPO="lucylq/qwen3_06B_lora_math"
 HF_ADAPTER_PATH=$(
   bash "$(dirname "${BASH_SOURCE[0]}")/download_hf_hub.sh" \
     --model_id "${HF_ADAPTER_REPO}" \
+    --revision 0e6bc3a88a597c5abc4872734eec8db3a9fdd846 \
     --files "adapter_config.json" "adapter_model.safetensors"
 )
 
 # Set environment variables for OmegaConf interpolation in yaml.
 export LORA_ADAPTER_CHECKPOINT="${HF_ADAPTER_PATH}/adapter_model.safetensors"
 export LORA_ADAPTER_CONFIG="${HF_ADAPTER_PATH}/adapter_config.json"
 
+# Without a checkpoint, export downloads Qwen/Qwen3-0.6B from its main branch,
+# so convert the pinned commit the read-only CI cache holds instead.
+QWEN_SNAPSHOT=$($PYTHON_EXECUTABLE -m executorch.examples.models.llama.hf_download \
+  snapshot Qwen/Qwen3-0.6B --revision c1899de289a04d12100db370d81485cdf75e47ca)
+QWEN_CHECKPOINT_DIR=$(mktemp -d "${RUNNER_TEMP:-/tmp}/qwen3_0_6b_XXXXXX")
+trap 'rm -rf "${QWEN_CHECKPOINT_DIR}"' EXIT
+QWEN_CHECKPOINT="${QWEN_CHECKPOINT_DIR}/qwen3_0_6b.pth"
+$PYTHON_EXECUTABLE -m executorch.examples.models.qwen3.convert_weights \
+  "${QWEN_SNAPSHOT}" "${QWEN_CHECKPOINT}"
+
 ### SINGLE LORA PTE ###
 # Export LoRA PTE file.
 $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
     --config examples/models/qwen3/config/qwen3_xnnpack_lora.yaml \
+    +base.checkpoint="${QWEN_CHECKPOINT}" \
     +export.output_name="qwen_lora_math_full.pte"
 
 # Capture the path of the downloaded qwen artifacts
-HF_QWEN_PATH=$(python -c "from huggingface_hub import snapshot_download; print(snapshot_download('unsloth/Qwen3-0.6B'))")
+HF_QWEN_PATH=$(python -c "from huggingface_hub import snapshot_download; print(snapshot_download('unsloth/Qwen3-0.6B', revision='db4e90b8359f816f09bf5c944797ce116f26da3c'))")
 echo "Model downloaded to: $HF_QWEN_PATH"
 
 ### BUILD LLAMA RUNNER.
@@ -120,6 +137,7 @@ fi
 # Export LoRA PTE, LoRA PTD, foundation PTD file.
 $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
     --config examples/models/qwen3/config/qwen3_xnnpack_lora.yaml \
+    +base.checkpoint="${QWEN_CHECKPOINT}" \
     +export.output_name="qwen_lora_math.pte" \
     +export.foundation_weights_file="qwen_foundation.ptd" \
     +export.lora_weights_file="qwen_lora_math.ptd"
@@ -179,6 +197,7 @@ The answer is: 12<|im_end|>"
 # and loading lora weights.
 $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
     --config examples/models/qwen3/config/qwen3_xnnpack_lora.yaml \
+    +base.checkpoint="${QWEN_CHECKPOINT}" \
     base.lora_config=null \
     +export.output_name="qwen_q.pte" \
     +export.foundation_weights_file="qwen_foundation_q.ptd" \
@@ -188,6 +207,7 @@ $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
 # Export Quantized LoRA PTE, LoRA PTD, foundation PTD file.
 $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
     --config examples/models/qwen3/config/qwen3_xnnpack_lora.yaml \
+    +base.checkpoint="${QWEN_CHECKPOINT}" \
     +export.output_name="qwen_lora_math_q.pte" \
     +export.foundation_weights_file="qwen_foundation_lora_q.ptd" \
     +export.lora_weights_file="qwen_lora_math_q.ptd" \
 
@@ -57,25 +57,42 @@ PY
 }
 
 # Download LoRA adapter.
+# The Hugging Face downloads below are pinned to commits the read-only
+# CI cache holds. To bump a pin, seed the cache first from a pytorch/executorch
+# branch (forks cannot write the cache): run pull.yml on it with
+# workflow_dispatch, or push to it after its pull request has the
+# ci-refresh-hf-cache label.
 python -m pip install -q huggingface_hub
 HF_ADAPTER_REPO="lucylq/qwen3_06B_lora_math"
 HF_ADAPTER_PATH=$(
   bash "$(dirname "${BASH_SOURCE[0]}")/download_hf_hub.sh" \
     --model_id "${HF_ADAPTER_REPO}" \
+    --revision 0e6bc3a88a597c5abc4872734eec8db3a9fdd846 \
     --files "adapter_config.json" "adapter_model.safetensors"
 )
 
 # Download base model (for tokenizer path).
-HF_QWEN_PATH=$(python -c "from huggingface_hub import snapshot_download; print(snapshot_download('unsloth/Qwen3-0.6B'))")
+HF_QWEN_PATH=$(python -c "from huggingface_hub import snapshot_download; print(snapshot_download('unsloth/Qwen3-0.6B', revision='db4e90b8359f816f09bf5c944797ce116f26da3c'))")
 echo "Model downloaded to: $HF_QWEN_PATH"
 
+# Without a checkpoint, export downloads Qwen/Qwen3-0.6B from its main branch,
+# so convert the pinned commit the read-only CI cache holds instead.
+QWEN_SNAPSHOT=$($PYTHON_EXECUTABLE -m executorch.examples.models.llama.hf_download \
+  snapshot Qwen/Qwen3-0.6B --revision c1899de289a04d12100db370d81485cdf75e47ca)
+QWEN_CHECKPOINT_DIR=$(mktemp -d "${RUNNER_TEMP:-/tmp}/qwen3_0_6b_XXXXXX")
+trap 'rm -rf "${QWEN_CHECKPOINT_DIR}"' EXIT
+QWEN_CHECKPOINT="${QWEN_CHECKPOINT_DIR}/qwen3_0_6b.pth"
+$PYTHON_EXECUTABLE -m executorch.examples.models.qwen3.convert_weights \
+  "${QWEN_SNAPSHOT}" "${QWEN_CHECKPOINT}"
+
 ### EXPORT MULTIMETHOD PTE ###
 # Set environment variables for OmegaConf interpolation in yaml.
 export LORA_ADAPTER_CHECKPOINT="${HF_ADAPTER_PATH}/adapter_model.safetensors"
 export LORA_ADAPTER_CONFIG="${HF_ADAPTER_PATH}/adapter_config.json"
 
 $PYTHON_EXECUTABLE -m extension.llm.export.export_llm \
-    --config examples/models/qwen3/config/qwen3_multimethod.yaml
+    --config examples/models/qwen3/config/qwen3_multimethod.yaml \
+    +base.checkpoint="${QWEN_CHECKPOINT}"
 
 ### BUILD LLAMA RUNNER ###
 cmake_install_executorch_libraries
 
@@ -12,5 +12,8 @@ source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
 
 source openvino/setupvars.sh
 cd backends/openvino/tests
-python test_runner.py --test_type ops
-python test_runner.py --test_type models
+# Run the model tests even when an op test fails, and still fail the job.
+status=0
+python test_runner.py --test_type ops || status=1
+python test_runner.py --test_type models || status=1
+exit "${status}"
@@ -47,6 +47,16 @@ fi
 
 MODEL_OUT=model.pte
 
+# Hugging Face Hub revisions, pinned. On OSDC runners HF_HUB_CACHE is a read-only
+# mount seeded with these snapshots, so downloading an unpinned repo fails with
+# "Read-only file system" as soon as the repo gets a new commit, even a README
+# edit (LiquidAI/LFM2.5-1.2B-Instruct on 2026-11-03). To move to a newer
+# revision, update it here and add the ci-refresh-hf-cache label to the PR so
+# the cache gets seeded.
+QWEN3_4B_REVISION=3d10de24598fff7a1ff7297103693fe1d2b82a5e
+PHI_4_MINI_REVISION=ca214ad7becf450bed20235bc677418a092a718a
+LFM2_5_1_2B_REVISION=0f604ada3f766f9f257460c4c9f0b5d6f69d431b
+
 
 # Default to XNNPACK
 BACKEND_ARGS="-X --xnnpack-extended-ops"
@@ -57,7 +67,7 @@ fi
 case "$MODEL_NAME" in
   qwen3_4b)
     echo "Running Qwen3-4B export..."
-    HF_MODEL_DIR=$(hf download pytorch/Qwen3-4B-INT8-INT4)
+    HF_MODEL_DIR=$(hf download pytorch/Qwen3-4B-INT8-INT4 --revision "${QWEN3_4B_REVISION}")
     EXPECTED_MODEL_SIZE_UPPER_BOUND=$((3 * 1024 * 1024 * 1024)) # 3GB
     $PYTHON_EXECUTABLE -m executorch.examples.models.qwen3.convert_weights \
       $HF_MODEL_DIR \
@@ -80,7 +90,7 @@ case "$MODEL_NAME" in
 
   phi_4_mini)
     echo "Running Phi-4-mini export..."
-    HF_MODEL_DIR=$(hf download pytorch/Phi-4-mini-instruct-INT8-INT4)
+    HF_MODEL_DIR=$(hf download pytorch/Phi-4-mini-instruct-INT8-INT4 --revision "${PHI_4_MINI_REVISION}")
     EXPECTED_MODEL_SIZE_UPPER_BOUND=$((3 * 1024 * 1024 * 1024)) # 3GB
     $PYTHON_EXECUTABLE -m executorch.examples.models.phi_4_mini.convert_weights \
       $HF_MODEL_DIR \
@@ -103,7 +113,7 @@ case "$MODEL_NAME" in
 
   lfm2_5_1_2b)
     echo "Running LFM2.5-1.2B export..."
-    HF_MODEL_DIR=$(hf download LiquidAI/LFM2.5-1.2B-Instruct)
+    HF_MODEL_DIR=$(hf download LiquidAI/LFM2.5-1.2B-Instruct --revision "${LFM2_5_1_2B_REVISION}")
     EXPECTED_MODEL_SIZE_UPPER_BOUND=$((2500 * 1024 * 1024)) # 2.5GB
     $PYTHON_EXECUTABLE -m executorch.examples.models.lfm2.convert_weights \
       $HF_MODEL_DIR \