vLLM v0.20.0 Highlights This release features 752 commits from 320 contributors (123 new)! DeepSeek V4: Initial DeepSeek V4 support landed (#40860), with DSML token-leakage fix in DSV4/3.2 (#40806), DSA + MTP IMA fix (#40772), and a silu clamp limit on the shared expert (#40950). CUDA 13.0 default: Default CUDA wheel on PyPI and `vllm/vllm-openai:v0.20.0` image switched to CUDA 13.0; architecture lists and build-args cleaned up (#39878), and CUDA bumped to 13.0.2 to match PyTorch 2.11.0 (#40669). As a general rule of thumb, our CUDA version policy follows PyTorch's. We highly recommend to install vLLM with `uv` and use `--torch-backend=cu129` if you are on CUDA 12.9.

PyTorch 2.11 upgrade (#34644): vLLM ships on torch 2.11 for CUDA, and XPU is now also on torch 2.11 (#37947) — XPU is no longer pinned to 2.10. This is a breaking change for environment dependency. Python 3.14: Added to the supported Python version list (#34770). Transformers v5: vLLM now runs on HuggingFace `transformers>=5` (#30566), with vision-encoder torch.compile bypass (#30518) and continued v4/v5 compat fixes including PaddleOCR-VL image processor `max_pixels` (#38629), Mistral YaRN warning (#37292), and Jina…