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.. _installation_guide:
Installation
============
**Prerequisites:** Linux · Python 3.9–3.13 · NVIDIA GPU (compute 7.0+) · CUDA 12.1+ · `uv <https://astral.sh/uv>`_
Install LMCache
---------------
.. tab-set::
.. tab-item:: Python (pip / uv)
.. tab-set::
.. tab-item:: Stable
.. tab-set::
.. tab-item:: CUDA 13.0
.. code-block:: bash
uv venv --python 3.12
source .venv/bin/activate
uv pip install lmcache
.. important::
You're all set! You can now start using LMCache. For hands-on guides and more
usage examples, see the :ref:`quickstart_examples` section.
.. note::
NIXL support (e.g. for disaggregated prefill and P2P KV
sharing) is an optional extra:
.. code-block:: bash
uv pip install lmcache[nixl]
.. tab-item:: CUDA 12.9
The CUDA 12.9 wheel is published to a dedicated
`GitHub Release <https://github.com/LMCache/LMCache/releases>`__ rather than PyPI.
.. code-block:: bash
uv venv --python 3.12
source .venv/bin/activate
VERSION=0.4.3 # replace with target release
uv pip install lmcache==${VERSION} \
--extra-index-url https://download.pytorch.org/whl/cu129 \
--find-links https://github.com/LMCache/LMCache/releases/expanded_assets/v${VERSION}-cu129 \
--index-strategy unsafe-best-match
.. note::
``--extra-index-url https://download.pytorch.org/whl/cu129`` ensures the CUDA 12.9
build of PyTorch is resolved. Without it, pip may select a mismatched CUDA variant.
.. tab-item:: Nightly
Nightly wheels are built from the latest ``dev`` branch each day at 07:30 UTC
and published to GitHub Releases. No version pinning required — ``--pre``
picks the latest nightly automatically.
.. tab-set::
.. tab-item:: CUDA 13.0
.. code-block:: bash
uv venv --python 3.12
source .venv/bin/activate
uv pip install lmcache --pre \
--extra-index-url https://download.pytorch.org/whl/cu130 \
--find-links https://github.com/LMCache/LMCache/releases/expanded_assets/nightly \
--index-strategy unsafe-best-match
.. tab-item:: CUDA 12.9
.. code-block:: bash
uv venv --python 3.12
source .venv/bin/activate
uv pip install lmcache --pre \
--extra-index-url https://download.pytorch.org/whl/cu129 \
--find-links https://github.com/LMCache/LMCache/releases/expanded_assets/nightly-cu129 \
--index-strategy unsafe-best-match
.. tab-item:: From Source
``--no-build-isolation`` ensures the kernels are compiled against the same torch
already installed in your environment, preventing undefined symbol errors at runtime.
.. tab-set::
.. tab-item:: CUDA 13.0
.. code-block:: bash
git clone https://github.com/LMCache/LMCache.git
cd LMCache
uv venv --python 3.12
source .venv/bin/activate
uv pip install -r requirements/build.txt
uv pip install vllm # pulls in required torch version (cu13)
uv pip install -e . --no-build-isolation
.. tab-item:: CUDA 12.9
.. code-block:: bash
git clone https://github.com/LMCache/LMCache.git
cd LMCache
uv venv --python 3.12
source .venv/bin/activate
uv pip install -r requirements/build.txt
# Pin vLLM (and torch) to the cu12.9 wheel index so the local
# CUDA 12 toolchain matches what the extensions are built against.
uv pip install vllm \
--extra-index-url https://download.pytorch.org/whl/cu129 \
--index-strategy unsafe-best-match
# LMCACHE_CUDA_MAJOR=12 makes setup.py pick cupy-cuda12x
# for install_requires instead of the cu13 default.
LMCACHE_CUDA_MAJOR=12 \
uv pip install -e . --no-build-isolation
.. tab-item:: ROCm
.. code-block:: bash
git clone https://github.com/LMCache/LMCache.git
cd LMCache
uv venv --python 3.12
source .venv/bin/activate
# Need to install these packages manually to avoid build isolation
uv pip install -r requirements/build.txt
# Install torch from the ROCm wheel index
uv pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm7.0
# Build LMCache. BUILD_WITH_HIP=1 makes setup.py pick cupy-rocm-7-0 automatically.
# PYTORCH_ROCM_ARCH selects the target GPU(s):
# gfx942 -> MI300X / MI325X
# gfx950 -> MI350X / MI355X
# Comma-separate to build a fat binary for multiple archs.
PYTORCH_ROCM_ARCH="gfx942,gfx950" \
TORCH_DONT_CHECK_COMPILER_ABI=1 \
CXX=hipcc \
BUILD_WITH_HIP=1 \
uv pip install -e . --no-build-isolation
.. tab-item:: Intel XPU
.. code-block:: bash
git clone https://github.com/LMCache/LMCache.git
cd LMCache
uv venv --python 3.12
source .venv/bin/activate
# Need to install these packages manually to avoid build isolation
uv pip install -r requirements/build.txt
# Build LMCache with SYCL backend.
BUILD_WITH_SYCL=1 uv pip install --no-build-isolation -e .
.. tab-item:: Docker
.. tab-set::
.. tab-item:: Stable
.. tab-set::
.. tab-item:: CUDA 13.0
.. code-block:: bash
docker pull lmcache/vllm-openai
.. tab-item:: CUDA 12.9
.. code-block:: bash
docker pull lmcache/vllm-openai:latest-cu129
.. tab-item:: Nightly
.. tab-set::
.. tab-item:: CUDA 13.0
.. code-block:: bash
docker pull lmcache/vllm-openai:latest-nightly
.. tab-item:: CUDA 12.9
.. code-block:: bash
docker pull lmcache/vllm-openai:latest-nightly-cu129
.. tab-item:: ROCm
.. code-block:: bash
docker pull rocm/vllm-dev:nightly_0624_rc2_0624_rc2_20250620
.. tab-item:: Intel XPU
.. code-block:: bash
docker pull intel/vllm:0.17.0-xpu
See :ref:`docker_deployment` for running the container and ROCm images.
.. tab-item:: CLI Only
Lightweight CLI-only package for querying or benchmarking a remote LMCache server.
No CUDA required, works on any OS.
.. code-block:: bash
pip install lmcache-cli
.. note::
``lmcache-cli`` and ``lmcache`` ship the same ``lmcache`` CLI command.
Do not install both in the same environment.
Build the Docker Image
----------------------
Instead of pulling a prebuilt image, you can build the LMCache (integrated with
vLLM) image yourself from the provided Dockerfile, located in
`docker/ <https://github.com/LMCache/LMCache/tree/dev/docker>`_.
From the root of the LMCache repository:
.. code-block:: bash
docker build --tag <IMAGE_NAME>:<TAG> --target image-build --file docker/Dockerfile .
Replace ``<IMAGE_NAME>`` and ``<TAG>`` with your desired image name and tag. See
the example build file in `docker/ <https://github.com/LMCache/LMCache/tree/dev/docker>`_
for an explanation of all build arguments.
Verify Installation
-------------------
.. code-block:: bash
python -c "import lmcache.c_ops"