diff --git a/.github/workflows/integration_test_8gpu_torchft.yaml b/.github/workflows/integration_test_8gpu_torchft.yaml
new file mode 100644
index 000000000..b06201ae7
--- /dev/null
+++ b/.github/workflows/integration_test_8gpu_torchft.yaml
@@ -0,0 +1,53 @@
+name: TorchFT 8 GPU Integration Test
+
+on:
+  push:
+    branches: [ main ]
+    paths:
+      - 'torchtitan/components/ft.py'
+  pull_request:
+    paths:
+      - 'torchtitan/components/ft.py'
+  schedule:
+    # Runs every 6 hours
+    - cron: '0 */6 * * *'
+concurrency:
+  group: unit-test${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number || github.ref }}
+  cancel-in-progress: true
+
+defaults:
+  run:
+    shell: bash -l -eo pipefail {0}
+
+jobs:
+  build-test:
+    uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
+    with:
+      runner: linux.g5.48xlarge.nvidia.gpu
+      gpu-arch-type: cuda
+      gpu-arch-version: "12.6"
+      # This image is faster to clone than the default, but it lacks CC needed by triton
+      # (1m25s vs 2m37s).
+      docker-image: torchtitan-ubuntu-20.04-clang12
+      repository: pytorch/torchtitan
+      upload-artifact: outputs
+      script: |
+        set -eux
+
+        # The generic Linux job chooses to use base env, not the one setup by the image
+        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
+        conda activate "${CONDA_ENV}"
+
+        pip config --user set global.progress_bar off
+
+        python -m pip install torchft-nightly
+        python -m pip install --force-reinstall --pre torch --index-url https://download.pytorch.org/whl/nightly/cu126
+        USE_CPP=0 python -m pip install --pre torchao --index-url https://download.pytorch.org/whl/nightly/cu126
+
+        mkdir artifacts-to-be-uploaded
+        echo "torchft_lighthouse"
+        RUST_BACKTRACE=1 torchft_lighthouse --min_replicas 1 --quorum_tick_ms 100 --join_timeout_ms 10000 > /dev/null 2>&1 &
+        echo "ft_integration_test"
+        # Getting error - Cuda failure 217 'peer access is not supported between these two devices'
+        python ./tests/integration_tests_ft.py artifacts-to-be-uploaded --ngpu 8
+        # pkill -9 torchft_lighthouse
diff --git a/tests/integration_tests_ft.py b/tests/integration_tests_ft.py
new file mode 100644
index 000000000..75005e738
--- /dev/null
+++ b/tests/integration_tests_ft.py
@@ -0,0 +1,159 @@
+# 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.
+
+import argparse
+import concurrent.futures
+import logging
+import os
+import subprocess
+from collections import defaultdict
+from dataclasses import dataclass
+from typing import Sequence
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+try:
+    import tomllib
+except ModuleNotFoundError:
+    import tomli as tomllib
+
+
+@dataclass
+class OverrideDefinitions:
+    """
+    This class is used to define the override definitions for the integration tests.
+    """
+
+    override_args: Sequence[Sequence[str]] = tuple(tuple(" "))
+    test_descr: str = "default"
+    test_name: str = "default"
+    ngpu: int = 4
+    model_flavor: str = "debugmodel"
+
+    def __repr__(self):
+        return self.test_descr
+
+
+def build_test_list():
+    """
+    key is the config file name and value is a list of OverrideDefinitions
+    that is used to generate variations of integration tests based on the
+    same root config file.
+    """
+    integration_tests_flavors = defaultdict(list)
+    integration_tests_flavors["debug_model.toml"] = [
+        OverrideDefinitions(
+            [
+                ["--training.steps 10", "--checkpoint.enable_checkpoint"],
+            ],
+            "Default TorchFT integration test",
+            "default_torchft",
+        )
+    ]
+    return integration_tests_flavors
+
+
+def _run_cmd(cmd):
+    return subprocess.run([cmd], text=True, shell=True)
+
+
+def run_test(test_flavor: OverrideDefinitions, full_path: str, output_dir: str):
+    # run_test supports sequence of tests.
+    test_name = test_flavor.test_name
+    dump_folder_arg = f"--job.dump_folder {output_dir}/{test_name}"
+    model_flavor_arg = f"--model.flavor {test_flavor.model_flavor}"
+
+    # Use all 8 GPUs in a single replica
+    # TODO: Use two replica groups
+    # Right now when passing CUDA_VISIBLE_DEVICES=0,1,2,3 and 4,5,6,7 for 2 RGs I get
+    # Cuda failure 217 'peer access is not supported between these two devices'
+    all_ranks = [",".join(map(str, range(0, 8)))]
+
+    for test_idx, override_arg in enumerate(test_flavor.override_args):
+        cmds = []
+
+        for replica_id, ranks in enumerate(all_ranks):
+            cmd = (
+                f'TORCH_TRACE="{output_dir}/{test_name}/compile_trace" '
+                + f"CUDA_VISIBLE_DEVICES={ranks}"
+                + f"CONFIG_FILE={full_path} NGPU={len(ranks)} ./run_train.sh "
+                + "--fault_tolerance.enable "
+                + f"--fault_tolerance.replica_id={replica_id} --fault_tolerance.group_size={len(all_ranks)}"
+            )
+
+            cmd += " " + dump_folder_arg
+            cmd += " " + model_flavor_arg
+            if override_arg:
+                cmd += " " + " ".join(override_arg)
+
+            logger.info(
+                "=====TorchFT Integration test, flavor : "
+                f"{test_flavor.test_descr}, command : {cmd}====="
+            )
+            cmds.append((replica_id, cmd))
+
+        with concurrent.futures.ProcessPoolExecutor(max_workers=2) as executor:
+            futures = [executor.submit(_run_cmd, cmd) for _, cmd in cmds]
+            results = [future.result() for future in futures]
+
+        for i, result in enumerate(results):
+            logger.info(result.stdout)
+
+            if result.returncode == 0:
+                continue
+
+            raise Exception(
+                f"Integration test {test_idx} failed, flavor : {test_flavor.test_descr}, command : {cmds[i]}"
+            )
+
+
+def run_tests(args):
+    integration_tests_flavors = build_test_list()
+
+    if args.ngpu < 8:
+        logger.info("Skipping TorchFT integration tests as we need 8 GPUs.")
+        return
+
+    for config_file in os.listdir(args.config_dir):
+        if not config_file.endswith(".toml"):
+            continue
+
+        full_path = os.path.join(args.config_dir, config_file)
+        with open(full_path, "rb") as f:
+            config = tomllib.load(f)
+            is_integration_test = config["job"].get("use_for_integration_test", False)
+            if not is_integration_test:
+                continue
+
+            for test_flavor in integration_tests_flavors[config_file]:
+                if not (args.test == "all" or test_flavor.test_name == args.test):
+                    continue
+
+                run_test(test_flavor, full_path, args.output_dir)
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("output_dir")
+    parser.add_argument(
+        "--config_dir", default="./torchtitan/models/llama3/train_configs"
+    )
+    parser.add_argument(
+        "--test",
+        default="all",
+        help="test to run, acceptable values: `test_name` in `build_test_list` (default: all)",
+    )
+    parser.add_argument("--ngpu", default=8, type=int)
+    args = parser.parse_args()
+
+    if not os.path.exists(args.output_dir):
+        os.makedirs(args.output_dir)
+    run_tests(args)
+
+
+if __name__ == "__main__":
+    main()