Bump vllm from 0.10.2 to 0.11.0 in /serving/docker

[dependabot]

Bumps vllm from 0.10.2 to 0.11.0.

Release notes

Sourced from vllm's releases.

v0.11.0

Highlights

This release features 538 commits, 207 contributors (65 new contributors)!

• This release completes the removal of V0 engine. V0 engine code including AsyncLLMEngine, LLMEngine, MQLLMEngine, all attention backends, and related components have been removed. V1 is the only engine in the codebase now.
• This releases turns on FULL_AND_PIECEWISE as the CUDA graph mode default. This should provide better out of the box performance for most models, particularly fine-grained MoEs, while preserving compatibility with existing models supporting only PIECEWISE mode.

Note: In v0.11.0 (and v0.10.2), --async-scheduling will produce gibberish output in some cases such as preemption and others. This functionality is correct in v0.10.1. We are actively fixing it for the next version.

Model Support

• New architectures: DeepSeek-V3.2-Exp (#25896), Qwen3-VL series (#24727), Qwen3-Next (#24526), OLMo3 (#24534), LongCat-Flash (#23991), Dots OCR (#24645), Ling2.0 (#24627), CWM (#25611).
• Encoders: RADIO encoder support (#24595), Transformers backend support for encoder-only models (#25174).
• Task expansion: BERT token classification/NER (#24872), multimodal models for pooling tasks (#24451).
• Data parallel for vision encoders: InternVL (#23909), Qwen2-VL (#25445), Qwen3-VL (#24955).
• Speculative decoding: EAGLE3 for MiniCPM3 (#24243) and GPT-OSS (#25246).
• Features: Qwen3-VL text-only mode (#26000), EVS video token pruning (#22980), Mamba2 TP+quantization (#24593), MRoPE + YaRN (#25384), Whisper on XPU (#25123), LongCat-Flash-Chat tool calling (#24083).
• Performance: GLM-4.1V 916ms TTFT reduction via fused RMSNorm (#24733), GLM-4 MoE SharedFusedMoE optimization (#24849), Qwen2.5-VL CUDA sync removal (#24741), Qwen3-VL Triton MRoPE kernel (#25055), FP8 checkpoints for Qwen3-Next (#25079).
• Reasoning: SeedOSS reason parser (#24263).

Engine Core

• KV cache offloading: CPU offloading with LRU management (#19848, #20075, #21448, #22595, #24251).
• V1 features: Prompt embeddings (#24278), sharded state loading (#25308), FlexAttention sliding window (#24089), LLM.apply_model (#18465).
• Hybrid allocator: Pipeline parallel (#23974), varying hidden sizes (#25101).
• Async scheduling: Uniprocessor executor support (#24219).
• Architecture: Tokenizer group removal (#24078), shared memory multimodal caching (#20452).
• Attention: Hybrid SSM/Attention in Triton (#21197), FlashAttention 3 for ViT (#24347).
• Performance: FlashInfer RoPE 2x speedup (#21126), fused Q/K RoPE 11% improvement (#24511, #25005), 8x spec decode overhead reduction (#24986), FlashInfer spec decode with 1.14x speedup (#25196), model info caching (#23558), inputs_embeds copy avoidance (#25739).
• LoRA: Optimized weight loading (#25403).
• Defaults: CUDA graph mode FULL_AND_PIECEWISE (#25444), Inductor standalone compile disabled (#25391).
• torch.compile: CUDA graph Inductor partition integration (#24281).

Hardware & Performance

• NVIDIA: FP8 FlashInfer MLA decode (#24705), BF16 fused MoE for Hopper/Blackwell expert parallel (#25503).
• DeepGEMM: Enabled by default (#24462), 5.5% throughput improvement (#24783).
• New architectures: RISC-V 64-bit (#22112), ARM non-x86 CPU (#25166), ARM 4-bit fused MoE (#23809).
• AMD: ROCm 7.0 (#25178), GLM-4.5 MI300X tuning (#25703).
• Intel XPU: MoE DP accuracy fix (#25465).

Large Scale Serving & Performance

• Dual-Batch Overlap (DBO): Overlapping computation mechanism (#23693), DeepEP high throughput + prefill (#24845).
• Data Parallelism: torchrun launcher (#24899), Ray placement groups (#25026), Triton DP/EP kernels (#24588).
• EPLB: Hunyuan V1 (#23078), Mixtral (#22842), static placement (#23745), reduced overhead (#24573).
• Disaggregated serving: KV transfer metrics (#22188), NIXL MLA latent dimension (#25902).
• MoE: Shared expert overlap optimization (#24254), SiLU kernel for DeepSeek-R1 (#24054), Enable Allgather/ReduceScatter backend for NaiveAllToAll (#23964).
• Distributed: NCCL symmetric memory with 3-4% throughput improvement (#24532), enabled by default for TP (#25070).

Quantization

• FP8: Per-token-group quantization (#24342), hardware-accelerated instructions (#24757), torch.compile KV cache (#22758), paged attention update (#22222).
• FP4: NVFP4 for dense models (#25609), Gemma3 (#22771), Llama 3.1 405B (#25135).
• W4A8: Faster preprocessing (#23972).

... (truncated)

Commits

• b8b302c Update CUDA architecture list in build pipeline for 12.9.1 wheels (#26592)
• f71952c [Build/CI] Revert back to Ubuntu 20.04, install python 3.12 with uv (#26103)
• d100776 [Bugfix] Disable cascade attention with FlashInfer (#26130)
• c75c2e7 [Deepseek v3.2] Support indexer prefill chunking (#25999)
• 9d9a2b7 [Small] Prevent bypassing media domain restriction via HTTP redirects (#26035)
• 6040e0b [BugFix] Fix FI accuracy issue when used for MLA prefill (#26063)
• 05bf0c5 Update base image to 22.04 (jammy) (#26065)
• c536881 [BugFix] ChunkedLocalAttention is currently not CG compatible (#26034)
• ebce361 [BugFix][DP/EP] Fix CUTLASS MLA hang under load (#26026)
• e4beabd [BugFix] Fix default kv-cache-dtype default for DeepseekV3.2 (#25988)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
  You can disable automated security fix PRs for this repo from the Security Alerts page.

[dependabot]

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.

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

[dependabot]

Looks like vllm is up-to-date now, so this is no longer needed.