chore: complete v0.21.0 → v0.22.0 version bump across all files
Update remaining Dockerfiles (cuda, rocm, xpu, ci) and docs (rocm.inc.md, cuda.inc.md, quickstart.md, gpu.md) that were missed in the initial pass — pip install lines, git checkout tags, Docker image tags, wheel URLs, and prose references. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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@@ -1,5 +1,5 @@
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ARG VLLM_BASE_IMAGE=vllm/vllm-openai
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ARG VLLM_BASE_TAG=v0.21.0
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ARG VLLM_BASE_TAG=v0.22.0
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FROM ${VLLM_BASE_IMAGE}:${VLLM_BASE_TAG}
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ARG APP_DIR=/workspace/vllm-omni
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WORKDIR ${APP_DIR}
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@@ -1,4 +1,4 @@
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ARG BASE_IMAGE=vllm/vllm-openai:v0.21.0
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ARG BASE_IMAGE=vllm/vllm-openai:v0.22.0
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FROM ${BASE_IMAGE}
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ARG COMMON_WORKDIR=/app
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@@ -1,4 +1,4 @@
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ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.21.0
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ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.22.0
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FROM ${BASE_IMAGE} AS base
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# Declare a variable to know if we want to use the nightly build or the stable build.
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@@ -88,7 +88,7 @@ ENV UV_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}
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ENV UV_INDEX_STRATEGY="unsafe-best-match"
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ENV UV_LINK_MODE="copy"
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ARG VLLM_VERSION=v0.21.0
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ARG VLLM_VERSION=v0.22.0
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RUN git clone -b ${VLLM_VERSION} https://github.com/vllm-project/vllm
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WORKDIR /workspace/vllm
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@@ -34,7 +34,7 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
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### Pre-built wheels
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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, and 0.21.0. 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).
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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, and 0.22.0. 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).
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=== "NVIDIA CUDA"
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@@ -39,13 +39,13 @@ uv pip install 'vllm-omni[demo]'
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# --8<-- [start:build-wheel-from-source]
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.21.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.22.0 release version of the library
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```bash
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uv pip install vllm==0.22.0 --torch-backend=auto
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```
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The 0.21.0 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.
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The 0.22.0 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.
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#### Installation of vLLM-Omni
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Since vllm-omni is rapidly evolving, it's recommended to install it from source
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@@ -66,12 +66,12 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.21.0
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git checkout v0.22.0
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```
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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.
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```bash
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#For CUDA 13.0 (the default for v0.21.0; the wheel filename has no `+cu130` suffix)
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.21.0/vllm-0.21.0-cp38-abi3-manylinux_2_35_x86_64.whl
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#For CUDA 13.0 (the default for v0.22.0; the wheel filename has no `+cu130` suffix)
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.22.0/vllm-0.22.0-cp38-abi3-manylinux_2_35_x86_64.whl
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```
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Install vllm with command below (If you have no existing PyTorch).
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```bash
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@@ -102,7 +102,7 @@ docker run --runtime nvidia --gpus 2 \
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--env "HF_TOKEN=$HF_TOKEN" \
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-p 8091:8091 \
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--ipc=host \
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vllm/vllm-omni:v0.21.0 \
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vllm/vllm-omni:v0.22.0 \
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vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
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```
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@@ -13,7 +13,7 @@ vLLM-Omni current recommends the steps in under setup through Docker Images.
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vLLM-Omni is built based on vLLM. Please install it with command below.
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```bash
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uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm722
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uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm722
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```
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#### Installation of vLLM-Omni
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@@ -34,13 +34,13 @@ uv pip install onnxruntime-rocm
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# --8<-- [start:build-wheel-from-source]
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.21.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.22.0 release version of the library
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```bash
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uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm722
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uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm722
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```
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The pre-built 0.21.0 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.
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The pre-built 0.22.0 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.
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#### Installation of vLLM-Omni
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Since vllm-omni is rapidly evolving, it's recommended to install it from source
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@@ -58,7 +58,7 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.21.0
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git checkout v0.22.0
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python3 -m pip install -r requirements/rocm.txt
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python3 setup.py develop
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```
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@@ -130,7 +130,7 @@ docker run --rm \
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-v ~/.cache/huggingface:/root/.cache/huggingface \
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--env "HF_TOKEN=$HF_TOKEN" \
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-p 8091:8091 \
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vllm/vllm-omni-rocm:v0.21.0 \
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vllm/vllm-omni-rocm:v0.22.0 \
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--model Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
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```
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@@ -149,7 +149,7 @@ docker run --rm -it \
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-v ~/.cache/huggingface:/root/.cache/huggingface \
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--env "HF_TOKEN=$HF_TOKEN" \
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--entrypoint bash \
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vllm/vllm-omni-rocm:v0.21.0
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vllm/vllm-omni-rocm:v0.22.0
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```
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# --8<-- [end:pre-built-images]
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@@ -22,7 +22,7 @@ source .venv/bin/activate
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uv pip install vllm==0.22.0 --torch-backend=auto
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# On ROCm
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uv pip install vllm==0.22.0+rocm721 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm721
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uv pip install vllm==0.22.0+rocm721 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm721
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git clone https://github.com/vllm-project/vllm-omni.git
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cd vllm-omni
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@@ -35,7 +35,7 @@ For additional installation methods — please see the [installation guide](inst
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!!! note
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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.
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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 < `0.21.0` and vLLM Omni `0.21.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue.
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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 < `0.22.0` and vLLM Omni `0.22.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue.
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## Offline Inference
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