docs: bump vLLM version references to v0.25.0 for the rebase

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 <noreply@anthropic.com>
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

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