diff --git a/.buildkite/hardware_tests/cpu.yaml b/.buildkite/hardware_tests/cpu.yaml
index 6189d5d61e6..19716bab6de 100644
--- a/.buildkite/hardware_tests/cpu.yaml
+++ b/.buildkite/hardware_tests/cpu.yaml
@@ -54,6 +54,20 @@ steps:
       pytest -x -v -s tests/models/language/generation -m cpu_model
       pytest -x -v -s tests/models/language/pooling -m cpu_model"
 
+- label: CPU-ModelRunnerV2 Tests
+  depends_on: []
+  device: intel_cpu
+  no_plugin: true
+  soft_fail: true
+  source_file_dependencies:
+  - vllm/v1/worker/cpu/
+  - vllm/v1/worker/gpu/
+  commands:
+    - |
+      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
+      uv pip install git+https://github.com/triton-lang/triton-cpu.git@270e696d
+      VLLM_USE_V2_MODEL_RUNNER=1 pytest -x -v -s tests/models/language/generation/test_granite.py -m cpu_model"
+
 - label: CPU-Quantization Model Tests
   depends_on: []
   device: intel_cpu
diff --git a/docker/Dockerfile.cpu b/docker/Dockerfile.cpu
index 8571a9c5d6d..c2ce0e88f29 100644
--- a/docker/Dockerfile.cpu
+++ b/docker/Dockerfile.cpu
@@ -27,11 +27,14 @@ WORKDIR /workspace
 ARG PYTHON_VERSION=3.12
 ARG PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
 
+ARG max_jobs=32
+ENV MAX_JOBS=${max_jobs}
+
 # Install minimal dependencies and uv
 RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
     --mount=type=cache,target=/var/lib/apt,sharing=locked \
     apt-get update -y \
-    && apt-get install -y --no-install-recommends sudo ccache git curl wget ca-certificates \
+    && apt-get install -y --no-install-recommends sudo ccache git curl wget ca-certificates zlib1g-dev \
     gcc-12 g++-12 libtcmalloc-minimal4 libnuma-dev ffmpeg libsm6 libxext6 libgl1 jq lsof make xz-utils \
     && update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12 \
     && curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -123,9 +126,6 @@ RUN --mount=type=cache,target=/root/.cargo/registry \
 ######################### BUILD IMAGE #########################
 FROM base AS vllm-build
 
-ARG max_jobs=32
-ENV MAX_JOBS=${max_jobs}
-
 ARG GIT_REPO_CHECK=0
 # Support for cross-compilation with x86 ISA including AVX2 and AVX512: docker build --build-arg VLLM_CPU_X86="true" ...
 ARG VLLM_CPU_X86=0
@@ -257,8 +257,7 @@ WORKDIR /vllm-workspace
 RUN --mount=type=cache,target=/root/.cache/uv \
     --mount=type=cache,target=/root/.cache/ccache \
     --mount=type=bind,from=vllm-build,src=/vllm-workspace/dist,target=dist \
-    uv pip install dist/*.whl && \
-    uv pip install "vllm[audio]"
+    uv pip install "$(realpath dist/*.whl)[audio,triton-cpu]"
 
 # Add labels to document build configuration
 LABEL org.opencontainers.image.title="vLLM CPU"
diff --git a/setup.py b/setup.py
index 3221c1d1bc0..a95ee3451b5 100644
--- a/setup.py
+++ b/setup.py
@@ -1195,6 +1195,11 @@ setup(
             "opentelemetry-exporter-otlp>=1.26.0",
             "opentelemetry-semantic-conventions-ai>=0.4.1",
         ],
+        "triton-cpu": [
+            "triton @ "
+            "git+https://github.com/triton-lang/triton-cpu.git@270e696d ; "
+            "platform_machine == 'x86_64'",
+        ],  # Remove after stable release
     },
     cmdclass=cmdclass,
     package_data=package_data,
diff --git a/vllm/platforms/cpu.py b/vllm/platforms/cpu.py
index ced97e03393..999bcfcc6db 100644
--- a/vllm/platforms/cpu.py
+++ b/vllm/platforms/cpu.py
@@ -14,6 +14,7 @@ from vllm.logger import init_logger
 from vllm.utils.cpu_resource_utils import (
     DEVICE_CONTROL_ENV_VAR,
     get_memory_node_info,
+    get_visible_memory_node,
 )
 from vllm.utils.mem_constants import GiB_bytes
 from vllm.v1.attention.backends.registry import AttentionBackendEnum
@@ -135,9 +136,13 @@ class CpuPlatform(Platform):
         scheduler_config.async_scheduling = False
 
         parallel_config = vllm_config.parallel_config
-        # OMP requires the MP executor to function correctly, UniProc is not
-        # supported as it is not possible to set the OMP environment correctly
-        if parallel_config.distributed_executor_backend == "uni":
+        if (
+            os.environ.get("VLLM_ENABLE_V1_MULTIPROCESSING", "1") == "1"
+            and parallel_config.distributed_executor_backend == "uni"
+        ):
+            # OMP requires the MP executor to function correctly, UniProc
+            # is not supported as it is not possible to set the OMP
+            # environment correctly
             parallel_config.distributed_executor_backend = "mp"
 
         if parallel_config.worker_cls == "auto":
@@ -481,3 +486,15 @@ class CpuPlatform(Platform):
             slot_mapping,
             isa,
         )
+
+    @classmethod
+    def get_current_memory_usage(
+        cls, device: torch.types.Device | None = None
+    ) -> float:
+        allowed_mem_node_list = get_visible_memory_node()
+        mem_status_list = [get_memory_node_info(i) for i in allowed_mem_node_list]
+        memory_usage = 0
+        for s in mem_status_list:
+            memory_usage += s.total_memory - s.available_memory
+
+        return memory_usage
diff --git a/vllm/triton_utils/importing.py b/vllm/triton_utils/importing.py
index e7c5fcb3982..8dea20fd3ea 100644
--- a/vllm/triton_utils/importing.py
+++ b/vllm/triton_utils/importing.py
@@ -3,6 +3,7 @@
 
 import os
 import types
+from importlib.metadata import version
 from importlib.util import find_spec
 
 from vllm.logger import init_logger
@@ -48,6 +49,17 @@ if HAS_TRITON:
                 len(active_drivers),
             )
             HAS_TRITON = False
+
+        # Check Triton CPU
+        if "cpu" in version("vllm"):
+            if "cpu" in backends:
+                HAS_TRITON = True
+            else:
+                logger.warning(
+                    "Triton is installed, but doesn't include CPU backend. "
+                    "Disabling Triton."
+                )
+                HAS_TRITON = False
     except ImportError:
         # This can occur if Triton is partially installed or triton.backends
         # is missing.
diff --git a/vllm/utils/platform_utils.py b/vllm/utils/platform_utils.py
index 6dd9ca4221c..cc69d9a241c 100644
--- a/vllm/utils/platform_utils.py
+++ b/vllm/utils/platform_utils.py
@@ -50,8 +50,10 @@ def is_pin_memory_available() -> bool:
 def is_uva_available() -> bool:
     """Check if Unified Virtual Addressing (UVA) is available."""
     # UVA requires pinned memory.
+    from vllm.platforms import current_platform
+
     # TODO: Add more requirements for UVA if needed.
-    return is_pin_memory_available()
+    return is_pin_memory_available() or current_platform.is_cpu()
 
 
 @cache
diff --git a/vllm/v1/worker/cpu/__init__.py b/vllm/v1/worker/cpu/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/vllm/v1/worker/cpu/buffer_utils.py b/vllm/v1/worker/cpu/buffer_utils.py
new file mode 100644
index 00000000000..8ee257a28f4
--- /dev/null
+++ b/vllm/v1/worker/cpu/buffer_utils.py
@@ -0,0 +1,16 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+from collections.abc import Sequence
+
+import torch
+
+from vllm.utils.platform_utils import is_uva_available
+
+
+class UvaBuffer:
+    def __init__(self, size: int | Sequence[int], dtype: torch.dtype):
+        if not is_uva_available():
+            raise RuntimeError("UVA is not available")
+        self.cpu = torch.zeros(size, dtype=dtype, device="cpu")
+        self.np = self.cpu.numpy()
+        self.uva = self.cpu
diff --git a/vllm/v1/worker/cpu/model_runner.py b/vllm/v1/worker/cpu/model_runner.py
new file mode 100644
index 00000000000..8aa0726a7f0
--- /dev/null
+++ b/vllm/v1/worker/cpu/model_runner.py
@@ -0,0 +1,16 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from vllm.logger import init_logger
+from vllm.v1.worker.gpu.model_runner import GPUModelRunner
+
+logger = init_logger(__name__)
+
+
+class CPUModelRunner(GPUModelRunner):
+    # TBD: Whether need to move this to Worker?
+    def warming_up_model(self) -> None:
+        logger.info("Warming up model for the compilation...")
+        # Only generate graph for the generic shape
+        self.profile_run()
+        logger.info("Warming up done.")
diff --git a/vllm/v1/worker/cpu/shm.py b/vllm/v1/worker/cpu/shm.py
new file mode 100644
index 00000000000..92aa1b5b95f
--- /dev/null
+++ b/vllm/v1/worker/cpu/shm.py
@@ -0,0 +1,62 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+# isort: skip_file
+# ruff: noqa: E402
+# mypy: disable-error-code="misc, assignment"
+
+from typing import Any
+
+# Patch torch APIs
+import torch
+
+
+def noop(*args: Any, **kwargs: Any) -> None:
+    pass
+
+
+class _EventPlaceholder:
+    def __init__(self, *args, **kwargs) -> None:
+        self.record = noop
+        self.synchronize = noop
+
+
+class _StreamPlaceholder:
+    def __init__(self, *args, **kwargs) -> None:
+        self.wait_stream = noop
+
+    def __enter__(self, *args, **kwargs):
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        pass
+
+
+torch.Event = _EventPlaceholder
+torch.cuda.Event = _EventPlaceholder
+torch.cuda.Stream = _StreamPlaceholder
+torch.cuda.set_stream = noop
+torch.cuda.current_stream = lambda *args, **kwargs: _StreamPlaceholder()
+torch.accelerator.synchronize = noop
+torch.accelerator.empty_cache = noop
+
+# Patch vLLM torch utils
+import vllm.utils.torch_utils as torch_utils
+
+
+def async_tensor_h2d(
+    data: list,
+    dtype: torch.dtype,
+    device: str | torch.device,
+    pin_memory: bool = False,
+) -> torch.Tensor:
+    return torch.tensor(data, dtype=dtype, device="cpu")
+
+
+torch_utils.async_tensor_h2d = async_tensor_h2d
+
+# Patch model runner APIs
+import vllm.v1.worker.gpu.buffer_utils as gpu_buffer_utils
+import vllm.v1.worker.cpu.buffer_utils as cpu_buffer_utils
+
+gpu_buffer_utils.UvaBuffer = cpu_buffer_utils.UvaBuffer
diff --git a/vllm/v1/worker/cpu_worker.py b/vllm/v1/worker/cpu_worker.py
index 1474d7ecb7a..9edb870a03a 100644
--- a/vllm/v1/worker/cpu_worker.py
+++ b/vllm/v1/worker/cpu_worker.py
@@ -1,5 +1,9 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+# Must be imported firstly
+import vllm.v1.worker.cpu.shm  # noqa # isort: skip
+
 import math
 import os
 import sys
@@ -101,6 +105,8 @@ class CPUWorker(Worker):
             )
 
     def init_device(self):
+        self.device = torch.device("cpu")
+
         # Check whether critical libraries are loaded
         def check_preloaded_libs(name: str):
             ld_preload_list = os.environ.get("LD_PRELOAD", "")
@@ -141,9 +147,16 @@ class CPUWorker(Worker):
         set_random_seed(self.model_config.seed)
 
         # Construct the model runner
-        self.model_runner: CPUModelRunner = CPUModelRunner(
-            self.vllm_config, torch.device("cpu")
-        )
+        if self.use_v2_model_runner:
+            from vllm.v1.worker.cpu.model_runner import (
+                CPUModelRunner as CPUModelRunnerV2,
+            )
+
+            self.model_runner: CPUModelRunner = CPUModelRunnerV2(  # type: ignore
+                self.vllm_config, self.device
+            )
+        else:
+            self.model_runner = CPUModelRunner(self.vllm_config, torch.device("cpu"))
 
     def sleep(self, level: int = 1) -> None:
         logger.warning("sleep mode is not supported on CPU, ignore it.")