diff --git a/.github/workflows/tritonbench-nightly.yml b/.github/workflows/tritonbench-nightly.yml
new file mode 100644
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--- /dev/null
+++ b/.github/workflows/tritonbench-nightly.yml
@@ -0,0 +1,65 @@
+name: TritonBench nightly (A100)
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: '00 18 * * *' # run at 6:00 PM UTC, K8s containers will roll out at 12PM EST
+
+jobs:
+  run-benchmark:
+    environment: docker-s3-upload
+    env:
+      BASE_CONDA_ENV: "torchbench"
+      CONDA_ENV:  "tritonbench-nightly"
+      PLATFORM_NAME: "gcp_a100"
+      SETUP_SCRIPT: "/workspace/setup_instance.sh"
+      TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN }}
+      AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
+      AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+      IS_GHA: 1
+      BUILD_ENVIRONMENT: benchmark-nightly
+    if: ${{ github.repository_owner == 'pytorch' }}
+    runs-on: [a100-runner]
+    steps:
+      - name: Checkout TorchBench
+        uses: actions/checkout@v3
+        with:
+          path: benchmark
+      - name: Tune Nvidia GPU
+        run: |
+          sudo nvidia-smi -pm 1
+          sudo nvidia-smi -ac 1215,1410
+          nvidia-smi
+      - name: Clone and setup conda env
+        run: |
+          CONDA_ENV=${BASE_CONDA_ENV} . "${SETUP_SCRIPT}"
+          conda create --name "${CONDA_ENV}" --clone "${BASE_CONDA_ENV}"
+      - name: Run the triton userbenchmark ci
+        run: |
+          . "${SETUP_SCRIPT}"
+          # remove old results if any
+          if [ -d benchmark-output ]; then rm -Rf benchmark-output; fi
+          pushd benchmark
+          if [ -d .userbenchmark ]; then rm -Rf .userbenchmark; fi
+          python run_benchmark.py triton --ci
+          cp -r ./.userbenchmark/triton ../benchmark-output
+      - name: Copy artifact and upload to scribe and Amazon S3
+        run: |
+          . "${SETUP_SCRIPT}"
+          pushd benchmark
+          LATEST_RESULT=$(find ../benchmark-output/ -name "metrics-*.json" | sort -r | head -1)
+          echo "Benchmark result file: ${LATEST_RESULT}"
+          # Upload the result json to Scribe
+          python ./scripts/userbenchmark/upload_scribe.py --userbenchmark_json "${LATEST_RESULT}" --userbenchmark_platform "${PLATFORM_NAME}"
+          # Upload the result json to Amazon S3
+          python ./scripts/userbenchmark/upload_s3.py --upload-file "${LATEST_RESULT}" --userbenchmark_platform "${PLATFORM_NAME}"
+      - name: Upload result to GH Actions Artifact
+        uses: actions/upload-artifact@v3
+        with:
+          name: TorchBench V3 result
+          path: benchmark-output/
+      - name: Clean up Conda env
+        if: always()
+        run: |
+          . "${SETUP_SCRIPT}"
+          conda deactivate && conda deactivate
+          conda remove -n "${CONDA_ENV}" --all