From b3f5c97deceec86819c7fed44f73f3b03e5ef281 Mon Sep 17 00:00:00 2001 From: tzhouam Date: Sun, 12 Jul 2026 10:14:21 +0800 Subject: [PATCH] docs: bump vLLM version references to v0.25.0 for the rebase MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Mirror of the docs update that shipped with the v0.24.0 rebase (#4709): - quickstart + CUDA/ROCm install guides: vllm==0.24.0 -> 0.25.0 pins, git checkout tag, precompiled-wheel URL (asset verified on the v0.25.0 GitHub release), and docker image tags - ROCm wheel index suffix changed upstream: rocm722 -> rocm723 (wheels.vllm.ai/rocm/0.25.0/ serves only rocm723; ROCm 7.2.2 -> 7.2.3) - gpu.md: add 0.25.0 to the pre-built wheels list NPU docs still reference v0.24.0 Ascend images intentionally — those images are published separately by the NPU team. Co-Authored-By: Claude Fable 5 Signed-off-by: tzhouam --- docs/getting_started/installation/gpu.md | 2 +- .../getting_started/installation/gpu/cuda.inc.md | 16 ++++++++-------- .../getting_started/installation/gpu/rocm.inc.md | 14 +++++++------- docs/getting_started/quickstart.md | 6 +++--- 4 files changed, 19 insertions(+), 19 deletions(-) diff --git a/docs/getting_started/installation/gpu.md b/docs/getting_started/installation/gpu.md index 4ef35398c..e21a11cee 100644 --- a/docs/getting_started/installation/gpu.md +++ b/docs/getting_started/installation/gpu.md @@ -34,7 +34,7 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr ### Pre-built wheels -Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, 0.21.0, 0.22.0, 0.23.0, and 0.24.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source). +Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, 0.21.0, 0.22.0, 0.23.0, 0.24.0, and 0.25.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source). === "NVIDIA CUDA" diff --git a/docs/getting_started/installation/gpu/cuda.inc.md b/docs/getting_started/installation/gpu/cuda.inc.md index 83cbcd68d..d4808139e 100644 --- a/docs/getting_started/installation/gpu/cuda.inc.md +++ b/docs/getting_started/installation/gpu/cuda.inc.md @@ -20,7 +20,7 @@ Therefore, it is recommended to install vLLM and vLLM-Omni with a **fresh new** vLLM-Omni is built based on vLLM. Please install it with command below. ```bash -uv pip install vllm==0.24.0 --torch-backend=auto +uv pip install vllm==0.25.0 --torch-backend=auto ``` #### Installation of vLLM-Omni @@ -39,13 +39,13 @@ uv pip install 'vllm-omni[demo]' # --8<-- [start:build-wheel-from-source] #### Installation of vLLM -If you do not need to modify source code of vLLM, you can directly install the stable 0.24.0 release version of the library +If you do not need to modify source code of vLLM, you can directly install the stable 0.25.0 release version of the library ```bash -uv pip install vllm==0.24.0 --torch-backend=auto +uv pip install vllm==0.25.0 --torch-backend=auto ``` -The 0.24.0 release of vLLM ships CUDA 13.0-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead. +The 0.25.0 release of vLLM ships CUDA 13.0-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead. #### Installation of vLLM-Omni Since vllm-omni is rapidly evolving, it's recommended to install it from source @@ -66,12 +66,12 @@ If you want to check, modify or debug with source code of vLLM, install the libr ```bash git clone https://github.com/vllm-project/vllm.git cd vllm -git checkout v0.24.0 +git checkout v0.25.0 ``` Set up environment variables to get pre-built wheels. If there are internet problems, just download the whl file manually. And set `VLLM_PRECOMPILED_WHEEL_LOCATION` as your local absolute path of whl file. ```bash -#For CUDA 13.0 (the default for v0.24.0; the wheel filename has no `+cu130` suffix) -export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.24.0/vllm-0.24.0-cp38-abi3-manylinux_2_28_x86_64.whl +#For CUDA 13.0 (the default for v0.25.0; the wheel filename has no `+cu130` suffix) +export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.25.0/vllm-0.25.0-cp38-abi3-manylinux_2_28_x86_64.whl ``` Install vllm with command below (If you have no existing PyTorch). ```bash @@ -102,7 +102,7 @@ docker run --runtime nvidia --gpus 2 \ --env "HF_TOKEN=$HF_TOKEN" \ -p 8091:8091 \ --ipc=host \ - vllm/vllm-omni:v0.24.0 \ + vllm/vllm-omni:v0.25.0 \ vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 ``` diff --git a/docs/getting_started/installation/gpu/rocm.inc.md b/docs/getting_started/installation/gpu/rocm.inc.md index af88e1e0c..4a64e8723 100644 --- a/docs/getting_started/installation/gpu/rocm.inc.md +++ b/docs/getting_started/installation/gpu/rocm.inc.md @@ -13,7 +13,7 @@ vLLM-Omni current recommends the steps in under setup through Docker Images. vLLM-Omni is built based on vLLM. Please install it with command below. ```bash -uv pip install vllm==0.24.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.24.0/rocm722 +uv pip install vllm==0.25.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.25.0/rocm723 ``` #### Installation of vLLM-Omni @@ -34,13 +34,13 @@ uv pip install onnxruntime-rocm # --8<-- [start:build-wheel-from-source] #### Installation of vLLM -If you do not need to modify source code of vLLM, you can directly install the stable 0.24.0 release version of the library +If you do not need to modify source code of vLLM, you can directly install the stable 0.25.0 release version of the library ```bash -uv pip install vllm==0.24.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.24.0/rocm722 +uv pip install vllm==0.25.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.25.0/rocm723 ``` -The pre-built 0.24.0 vLLM wheel targets ROCm 7.2.2. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead. +The pre-built 0.25.0 vLLM wheel targets ROCm 7.2.3. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead. #### Installation of vLLM-Omni Since vllm-omni is rapidly evolving, it's recommended to install it from source @@ -58,7 +58,7 @@ If you want to check, modify or debug with source code of vLLM, install the libr ```bash git clone https://github.com/vllm-project/vllm.git cd vllm -git checkout v0.24.0 +git checkout v0.25.0 python3 -m pip install -r requirements/rocm.txt python3 setup.py develop ``` @@ -130,7 +130,7 @@ docker run --rm \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=$HF_TOKEN" \ -p 8091:8091 \ - vllm/vllm-omni-rocm:v0.24.0 \ + vllm/vllm-omni-rocm:v0.25.0 \ --model Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 ``` @@ -149,7 +149,7 @@ docker run --rm -it \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=$HF_TOKEN" \ --entrypoint bash \ - vllm/vllm-omni-rocm:v0.24.0 + vllm/vllm-omni-rocm:v0.25.0 ``` # --8<-- [end:pre-built-images] diff --git a/docs/getting_started/quickstart.md b/docs/getting_started/quickstart.md index 2c7f278ca..914f1f7b4 100644 --- a/docs/getting_started/quickstart.md +++ b/docs/getting_started/quickstart.md @@ -19,10 +19,10 @@ uv venv --python 3.12 --seed source .venv/bin/activate # On CUDA -uv pip install vllm==0.24.0 --torch-backend=auto +uv pip install vllm==0.25.0 --torch-backend=auto # On ROCm -uv pip install vllm==0.24.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.24.0/rocm722 +uv pip install vllm==0.25.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.25.0/rocm723 git clone https://github.com/vllm-project/vllm-omni.git cd vllm-omni @@ -34,7 +34,7 @@ For additional installation methods — please see the [installation guide](inst !!! note It is important to install the same major & minor version of vLLM and vLLM Omni, otherwise things may not work as expected. If the versions are misaligned, you will see a warning when you import vLLM Omni. - If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.24.0` and vLLM Omni `0.24.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue. + If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.25.0` and vLLM Omni `0.25.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue. ## Offline Inference