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chore(deps): update vllm/vllm-openai docker tag to v0.25.1#136

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chore(deps): update vllm/vllm-openai docker tag to v0.25.1#136
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This PR contains the following updates:

Package Type Update Change
vllm/vllm-openai (source) Kustomization minor v0.23.0v0.25.1

Release Notes

vllm-project/vllm (vllm/vllm-openai)

v0.25.1

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vLLM v0.25.1

Highlights

This release features 2 commits from 2 contributors (1 new)!

v0.25.1 is a patch release containing two targeted bug fixes on top of v0.25.0.

Bug Fixes
  • Avoid blocking model launching when no system FFmpeg is available for TorchCodec (#​47888). Previously import torchcodec raised a RuntimeError at import time when system FFmpeg was missing, which blocked startup (e.g. vllm serve Qwen/Qwen3-VL-2B-Instruct) even when TorchCodec was not in use. The error is now deferred to runtime so it only surfaces if TorchCodec is actually needed.
  • Guard mixed-dtype allreduce RMSNorm quant fusions (#​48330). The fused FlashInfer allreduce + RMSNorm + static-quantization patterns could match graphs where the activation and RMSNorm weight dtypes differ (e.g. a BF16 residual stream with an FP32 Gemma/Qwen-style RMSNorm weight in NVFP4 models), corrupting the hidden state and producing garbage output such as repeated !!!!! tokens. A dtype-match guard now routes incompatible mixed-dtype graphs to the safe path, while same-dtype models retain the full allreduce + RMSNorm + quant fusion.

Contributors

@​Isotr0py, @​hugo-cen

New Contributors

v0.25.0

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vLLM v0.25.0 Release Notes

Highlights

This release features 558 commits from 232 contributors (64 new)!

  • Model Runner V2 is now the default for all dense models (#​44443). Building on quantized-model support from the previous release, MRv2 is now the standard execution path, with new support for EVS (#​46535), realtime embeddings (#​46762), prefix caching for Mamba hybrid models (#​42406), multimodal-prefix bidirectional attention (#​46942), and dynamic speculative decoding compatible with full CUDA graphs (#​45953).
  • PagedAttention has been removed (#​47361). The legacy attention implementation is deleted now that V1/MRv2 backends are the standard path.
  • The Transformers modeling backend is now as fast as native vLLM (#​47187), and gained FP8 MoE support (#​46820), CUDA graph + embed scaling fixes (#​48010), and migration of GPTBigCode/Starcoder2 (#​30966) and RoBERTa (#​47452).
  • New models: LLaVA-OneVision-2 (#​44785), Unlimited OCR (#​46564, #​47102), MOSS-Transcribe-Diarize (#​47729), openai/privacy-filter (#​41026), and Hy3 (#​47192). GLM-5 / DeepSeek-V3.2 landed in the model zoo (#​46808) with GLM-5.2 tuning, and MiniMax-M3 gained pipeline parallelism (#​45810) and NVFP4 support (#​46756).
  • New Streaming Parser Engine (#​46610) — a unified tool-call/reasoning parsing framework, with a new Kimi k2.5/k2.6/k2.7 parser and ports of seed_oss (#​46314) and DeepSeek V4 (#​45877). The Rust frontend continues to mature with HTTPS/mTLS (#​45890), a DP supervisor (#​47076), and profiler control routes (#​46306).
  • Universal speculative decoding for heterogeneous vocabularies (TLI) (#​38174), plus new DSpark (#​46995) and DFlash (#​46770, #​46853) drafters.
Model Support
Engine Core
Hardware & Performance
  • GLM-5.2 / DeepSeek: fused_indexer_q_rope_quant Triton kernel (1.9–3.3% E2E throughput) (#​46862), reduce-scatter MoE all-reduce (3.1–3.2% E2E) (#​46635), op fusion for GLM5/DSV3.2 (#​46876), token_to_req_indices cache for DSv4 (5–6x kernel speedup) (#​47474), better DSv4 MXFP8 kernel (#​47229), redundant-op removal (#​47198, #​46651).
  • NVIDIA/Blackwell: FlashInfer fused all-reduce tuned for world_size=16 on GB300 (#​46392), restored NVFP4 swizzled-scale zero-init to recover Blackwell decode throughput (#​45739), CuTeDSL/FA4-MLA warmup infrastructure (#​46182), skip cooperative top-K on SM120 (#​47164), B12x backend for non-gated MoEs (#​43328).
  • Kernels: Helion fused_qk_norm_rope (#​44010) and silu_and_mul_per_block_quant (#​43994), Triton MLA logits workspace (#​46819), swap-AB optimization for fused MoE (#​36559), vectorized fp32 moe_sum supporting any top-k (#​46643), blocking CUDA events to avoid busy-polling the driver lock (#​47081).
  • AMD/ROCm: moved to torch 2.11 stable ABI (#​47128); AITER FlashAttention MLA prefill backend ROCM_AITER_FA (#​45033); fused shared-expert for GLM-4.5/6/7 (#​44313) and MiniMax-M3 (#​46474, #​46545); AITER MoE optimization for DeepSeek-V4 (#​46122); AITER custom all-reduce in CudaCommunicator (#​46065); INT3 quantization for quickreduce (#​45666).
  • Intel XPU: W8A8 FP8 linear kernel with multi-granularity quant (#​43645), pipeline-parallel accuracy fix (#​47253), uniform-batch CUDA graph for FA2 (#​46555), route mm_prefix models to Triton attention (#​47688), C++ get_memory_info (#​47134).
  • CPU: accelerated unquantized MoE for AArch64 (#​46353), macOS/Apple Silicon hang fix via OpenMP (#​46769) and broken-install fix (#​47457), compressed-tensor w8a8 int8 MoE (#​42920), Mamba ShortConv (#​35059), chunked prefill + prefix caching for Qwen3.5 (#​46202), faster gelu via tanh AOR (#​44639).
  • RISC-V: RVV path for W4A8 INT4 GEMM (#​45269), BF16 on VLEN=256 hardware (#​45243), reduced LMUL pressure in INT4 LUT dequant (#​47538). POWER: fp16 support on PowerPC (#​46135).
  • Platform: accelerator-agnostic get_memory_info (#​44825).
Large Scale Serving & Distributed
  • Sequence parallelism without requiring DP, 1.9–5.0% E2E throughput improvement (#​47070).
  • Distributed: NCCL symmetric memory extended to AllGather and ReduceScatter (#​46703), FlashInfer all-reduce defaults to MNNVL on single node (#​47219, #​47589), fault-tolerance backend to detect all2all peer faults and prevent corrupted output (#​43637).
  • Data parallel: throttle prefills based on local prefill work (#​46532), rotate load-balancer tie-break to avoid engine bias (#​47420), DP supervisor via the Rust frontend (#​47076), DP MTP hang fix (#​40589).
  • PD disaggregation: secondary-tier implementation (#​42285), Mooncake connector GDN (Qwen3.5) + MLA (DeepSeek-V4-Flash) support (#​46807), NIXL Mamba1 support (#​45019), MultiConnector kv_transfer_params merging (#​46777), usage field exposed for disaggregated serving (#​42748).
  • DCP: FlashInfer MLA support (#​43729), FLASHINFER_MLA_SPARSE support (#​46076), LSE log-base fixes (#​47079); Mooncake parallelized KV load (#​45971) and DCP>1 lookup fix (#​46855).
  • ROCm: stabilized high-throughput DBO for DP+EP (#​46990), EPLB for Quark OCP MXFP4 MoE (#​47220).
Quantization
  • 2/3/5/6/7-bit pack-quantized weight-only inference (Humming) (#​46389), Triton INT4 per-token-head KV cache quantization (#​40835).
  • NVFP4: fused weight dequantization with compute in the MoE MLP Triton kernel (#​44667), NVFP4 KV cache with skip-layers sliding window (#​42890), MiniMax-M3 ModelOpt NVFP4 support (#​46756).
  • FP8: weights padding for per-block online quantization (#​44763); deprecated the old FP8 online MoE quantization class (#​44514).
  • Marlin: thread-tile padding extended to MoE (WNA16 + FP8/MXFP8) (#​45703), int8 grouped WNA16 MoE (#​47154); FlashInfer MXINT4 MoE for gated SiLU (#​46518).
  • Fixes: W8A8 int-quant scheme-selection regression (#​46860), tied quantized embeddings for ModelOpt Gemma4 (#​45544), NVFP4+MTP crash on Qwen3Next (#​46316), ModelOpt mixed-precision for sparse configs (#​47318), CPU w4a8_int8 MoE path (#​46739), actionable error on group-size/TP mismatch (#​46230).
API & Frontend
  • Streaming Parser Engine (#​46610): unified tool-call/reasoning parsing with a new Kimi k2.5/k2.6/k2.7 parser; ported seed_oss (#​46314) and DeepSeek V4 (#​45877).
  • OpenAI compatibility: Responses API namespace tools (#​47024), per-request timing metrics field on Chat/Completions responses (#​46768), token offsets on render endpoints (#​44226), return_loss_mask for training-data generation (#​46846), HTTP 422 for unprocessable image URLs (#​47165).
  • gpt-oss / Harmony: dedicated Harmony renderer (#​46800), process_eos() flush (#​46437), raw-output recovery on non-terminal parse (#​47062, #​47379).
  • Rust frontend: static HTTPS and mTLS for HTTP and gRPC (#​45890), DP supervisor (#​47076), profiler control routes (#​46306), repetition_detection sampling param (#​46684), unified/combined parser interface (#​46583), reduced multimodal tensor copies (#​47581), plus many parser and validation fixes.
  • Video: TorchCodec added as a video decoding backend (#​46609).
  • CLI/UX: TTFT and TPS printing in vllm chat (#​46775), model_class_overrides for development/debugging (#​47148).
  • Tooling/validation: many tool-parser fixes (Kimi K2 IDs #​46344, PoolsideV1 #​46486/#​47311, non-ASCII arguments #​46308, thinking_token_budget re-entry #​43757); rejection of invalid config values (#​44070, #​44002, #​46612) and degenerate structured_outputs that crash EngineCore (#​45346).
Security
  • Prevent image decompression-bomb OOM denial of service (#​47010).
  • Prevent an infinite loop in split_audio with NaN audio samples (#​46463).
  • Bound tokenizer work when an explicit truncation_side is set (#​47007).
  • Block request-level GPU video backend selection (#​47259).
  • Document the gRPC interface as insecure, for private use only (#​45903).
Dependencies
  • FlashInfer 0.6.13 (#​46683), tpu-inference v0.23.0 (#​46568), aiter 0.1.16.post2 (#​46692), vllm_xpu_kernels v0.1.10.1 (#​46607), huggingface-hub v1.22.0 (#​47551).
  • DeepGEMM updated to enable SM120 support (#​47304), FlashAttention 3 built against the torch stable API (#​46644), Rust frontend TLS switched from rustls to native-tls/OpenSSL (#​46696).
Deprecations & Removals

New Contributors

Contributors

Thank you to all the contributors who made this release possible!

@​AndreasKaratzas, @​njhill, @​BugenZhao, @​hmellor, @​yewentao256, @​WoosukKwon, @​Sunt-ing, @​micah-wil, @​mgoin, @​reidliu41, @​peizhang56, @​mawong-amd, @​TheEpicDolphin, @​jeejeelee, @​taneem-ibrahim, @​chaunceyjiang, @​chaojun-zhang, @​divakar-amd, @​fxmarty-amd, @​LopezCastroRoberto, @​wzhao18, @​mayuyuace, @​jperezdealgaba, @​noooop, @​yzong-rh, @​jikunshang, @​zxd1997066, @​bigPYJ1151, @​yma11, @​hickeyma, @​benchislett, @​xianbaoqian, @​andakai, @​NickLucche, @​ivanium, @​joerowell, @​EazyReal, @​mganczarenko, @​majunze2001, @​hongxiayang, @​WindChimeRan, @​Rohan138, @​tjtanaa, @​bbrowning, @​thisjiang, @​Fangzhou-Ai, @​blasrodri, @​Isotr0py, @​zhenwei-intel, @​zyongye, @​frida-andersson, @​muhammadfawaz1, @​lcheng321, @​spandantiwari, @​Palaiologos1453, @​soaringk, @​Lynn-hh, @​fadara01, @​djramic, @​Liangliang-Ma, @​ronensc, @​aarushjain29, @​HDCharles, @​qianlihuang, @​AgenticSpark, @​charlifu, @​cleonard530, @​shen-shanshan, @​xaguilar-amd, @​xiaohongchen1991, @​varun-sundar-rabindranath, @​gau-nernst, @​tahsintunan, @​GirasoleY, @​hclsys, @​Yejing-Lai, @​LucasWilkinson, @​matteso1, @​akii96, @​atalman, @​lucianommartins, @​I3eg1nner, @​rahulssv-ibm, @​ZichenYuan, @​tanpinsiang, @​hillelda, @​Srinivasoo7, @​Etelis, @​Rukhaiya2004, @​Oxygen56, @​Priyjain-amd, @​GuyStone, @​nholmber, @​CienetStingLin, @​xinyu-intel, @​JartX, @​esmeetu, @​hhhhhhhhhhhhhhhhho, @​harsha20032020, @​walterbm, @​Acaciasama, @​jessiewei7, @​ashwin-phadke, @​shivampr, @​cyq1017, @​kjiang249, @​orestis-z, @​xyang16, @​tianmu-li, @​mgehre-amd, @​aaarkai, @​guybd, @​wcynb1023, @​Josephasafg, @​qyYue1389, @​russellb, @​haoyangli0109, @​sfeng33, @​mikekg, @​EanWang211123, @​ovidiusm, @​ItsMatti4, @​hyeongyun0916, @​qli88, @​juliendenize, @​calvarado2004, @​tdoublep, @​brandonpelfrey, @​davispuh, @​weizhoublue, @​jasonozuzu-cohere, @​wentian-byte, @​skajre, @​gty111, @​omirosh, @​decarpentierg, @​fjosw, @​ilmarkov, @​yuwenzho, @​JisoLya, @​JohnLangford, @​aldenlobo, @​bnellnm, @​jasonlizhengjian, @​zufangzhu, @​izhuhaoran, @​MatthewBonanni, @​deng451e, @​ashwing, @​sriganesh123, @​linitra24, @​liranschour, @​umarkovi-amd, @​aman0603, @​adobrzyn, @​jwzheng96, @​eicherseiji, @​ArsalanShakil, @​tc-mb, @​imargulis, @​fangyuchu, @​puririshi98, @​JeanPaulShapo, @​VectorPeak, @​tarjan1, @​qiching, @​Achyuthan-S, @​ZJY0516, @​lucifer1004, @​cinnamonica02, @​jmamou, @​almayne, @​hao-aaron, @​Jyothirmaikottu, @​andylolu2, @​AIvashov, @​stevenkuang-tencent, @​lcskrishna, @​Aneureka, @​wan-danfeng, @​chengzheng345, @​pranavthakur0-0, @​zRzRzRzRzRzRzR, @​DanBlanaru, @​adamkbaranowski, @​wendyliu235, @​eparshut, @​yangyang-cs95, @​kalyanamdewri, @​maxdebayser, @​fenghourun, @​tpopp, @​okorzh-amd, @​labAxiaoming, @​sychen52, @​ekagra-ranjan, @​gausah01, @​yuyue0225sc, @​cpersson-amd, @​lslusarczyk, @​alex101-ops, @​Zhenzhong1, @​velonica0, @​zhongjing123, @​zhou9402, @​llsj14, @​majian4work, @​akinsella, @​BadrBasowid, @​afierka-intel, @​ayush1399, @​LiJzd, @​jesco-absolut, @​Laurent-Zhang, @​Kevin-XiongC, @​NathanielMcVicar, @​askliar, @​ACEEE-1222, @​jinzhen-lin, @​SherryC41, @​simondanielsson, @​nv-nedelman-1, @​yisustc, @​kylesayrs, @​jialoop-git, @​NicolasHug, @​guan404ming, @​HumphreySun98, @​danielafrimi, @​gcanlin, @​robertgshaw2-redhat

v0.24.0

Compare Source

vLLM v0.24.0 Release Notes

Highlights

This release features 571 commits from 256 contributors (77 new)!

  • MiniMax-M3: Added support for the new MiniMax-M3 model (#​45381), with a fast follow-on of BF16/FP8 indexer via MSA (#​45892), MXFP4 support (#​45896), FP8 sparse GQA (#​45744), and extensive AMD/ROCm tuning — mxfp8 MoE/linear on gfx950 (#​45725), fp8_per_channel for bf16 weights on MI300X (#​45854), FP8 KV-cache fix (#​45720), and packed-modules mapping (#​45794). A MiniMax-M2 perf regression was also fixed ([#​45935](https://redirect.g

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@konflux-internal-p02
konflux-internal-p02 Bot force-pushed the konflux/mintmaker/rhoai-3.5/vllm-vllm-openai-0.x branch from 95d2a49 to 24faf98 Compare July 14, 2026 12:53
@konflux-internal-p02 konflux-internal-p02 Bot changed the title chore(deps): update vllm/vllm-openai docker tag to v0.24.0 chore(deps): update vllm/vllm-openai docker tag to v0.25.0 Jul 14, 2026
Signed-off-by: konflux-internal-p02 <170854209+konflux-internal-p02[bot]@users.noreply.github.com>
@konflux-internal-p02
konflux-internal-p02 Bot force-pushed the konflux/mintmaker/rhoai-3.5/vllm-vllm-openai-0.x branch from 24faf98 to 506295d Compare July 17, 2026 00:42
@konflux-internal-p02 konflux-internal-p02 Bot changed the title chore(deps): update vllm/vllm-openai docker tag to v0.25.0 chore(deps): update vllm/vllm-openai docker tag to v0.25.1 Jul 17, 2026
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