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@dependabot dependabot bot commented on behalf of github May 28, 2025

Updates the requirements on vllm to permit the latest version.

Release notes

Sourced from vllm's releases.

v0.9.0

Highlights

This release features 649 commits, from 215 contributors (82 new contributors!)

  • vLLM has upgraded to PyTorch 2.7! (#16859) This is a breaking change for environment dependency.
    • The default wheel has been upgraded from CUDA 12.4 to CUDA 12.8. We will distribute CUDA 12.6 wheel on GitHub artifact.
    • As a general rule of thumb, our CUDA version policy follow PyTorch's CUDA version policy.
  • Enhanced NVIDIA Blackwell support. vLLM now ships with initial set of optimized kernels on NVIDIA Blackwell with both attention and mlp.
    • You can use our docker image or install FlashInfer nightly wheel pip install https://download.pytorch.org/whl/cu128/flashinfer/flashinfer_python-0.2.5%2Bcu128torch2.7-cp38-abi3-linux_x86_64.whl then set VLLM_ATTENTION_BACKEND=FLASHINFER for better performance.
    • Upgraded support for the new FlashInfer main branch. (#15777)
    • Please checkout vllm-project/vllm#18153 for the full roadmap
  • Initial DP, EP, PD support for large scale inference
    • EP:
      • Permute and unpermute kernel for moe optimization (#14568)
      • Modularize fused experts and integrate PPLX kernels (#15956)
      • Refactor pplx init logic to make it modular (prepare for deepep) (#18200)
      • Add ep group and all2all interface (#18077)
    • DP:
      • Decouple engine process management and comms (#15977)
    • PD:
      • NIXL Integration (#17751)
      • Local attention optimization for NIXL (#18170)
      • Support multiple kv connectors (#17564)
  • Migrate docs from Sphinx to MkDocs (#18145, #18610, #18614, #18616. #18622, #18626, #18627, #18635, #18637, #18657, #18663, #18666, #18713)

Notable Changes

  • Removal of CUDA 12.4 support due to PyTorch upgrade to 2.7.
  • Change top_k to be disabled with 0 (still accept -1 for now) (#17773)
  • The seed is now set to 0 by default for V1 Engine, meaning that different vLLM runs now yield the same outputs even if temperature > 0. This does not modify the random state in user code since workers are run in separate processes unless VLLM_USE_V1_MULTIPROCESSING=0. (#17929, #18741)

Model Enhancements

  • Support MiMo-7B (#17433), MiniMax-VL-01 (#16328), Ovis 1.6 (#17861), Ovis 2 (#15826), GraniteMoeHybrid 4.0 (#17497), FalconH1* (#18406), LlamaGuard4 (#17315)
    • Please install the development version of transformers (from source) to use Falcon-H1.
  • Embedding models: nomic-embed-text-v2-moe (#17785), new class of gte models (#17986)
  • Progress in Hybrid Memory Allocator (#17394, #17479, #17474, #17483, #17193, #17946, #17945, #17999, #18001, #18593)
  • DeepSeek: perf enhancement by moving more calls into cuda-graph region(#17484, #17668), Function Call (#17784), MTP in V1 (#18435)
  • Qwen2.5-1M: Implements dual-chunk-flash-attn backend for dual chunk attention with sparse attention support (#11844)
  • Qwen2.5-VL speed enhancement via rotary_emb optimization (#17973)
  • InternVL-Qwen2.5 models now support video inputs (#18499)

Performance, Production and Scaling

  • Support full cuda graph in v1 (#16072)
  • Pipeline Parallelism: MultiprocExecutor support (#14219), torchrun (#17827)
  • Support sequence parallelism combined with pipeline parallelism (#18243)
  • Async tensor parallelism using compilation pass (#17882)
  • Perf: Use small max_num_batched_tokens for A100 (#17885)
  • Fast Model Loading: Tensorizer support for V1 and LoRA (#17926)
  • Multi-modality: Automatically cast multi-modal input dtype before transferring device (#18756)

Security

... (truncated)

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@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels May 28, 2025
@mergify mergify bot added the ci-failure label May 28, 2025
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booxter commented May 31, 2025

@Mergifyio rebase

Updates the requirements on [vllm](https://github.com/vllm-project/vllm) to permit the latest version.
- [Release notes](https://github.com/vllm-project/vllm/releases)
- [Changelog](https://github.com/vllm-project/vllm/blob/main/RELEASE.md)
- [Commits](vllm-project/vllm@v0.1.0...v0.9.0)

---
updated-dependencies:
- dependency-name: vllm
  dependency-version: 0.9.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
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mergify bot commented May 31, 2025

rebase

✅ Branch has been successfully rebased

@booxter booxter force-pushed the dependabot/pip/vllm-lte-0.9.0 branch from f64c30f to c5f2417 Compare May 31, 2025 01:23
@mergify mergify bot removed the ci-failure label May 31, 2025
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Bad bot

@booxter booxter closed this Jun 4, 2025
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dependabot bot commented on behalf of github Jun 4, 2025

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.

@dependabot dependabot bot deleted the dependabot/pip/vllm-lte-0.9.0 branch June 4, 2025 14:15
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