vLLM 0.31.0

Original release notes

v0.31.0

Highlights

This release features 717 commits from 307 contributors (96 new)!

DeepSeek-V4.1-Flash performance: FlashMLA mega attention with the V4.1 NVFP4 compressed KV cache is now the SM100 default (#56935); DeepGEMM sparse MQA logits for the indexer (#56254) and Mega-Gate fusing the gate GEMM with expert selection (#56266); decoder boundaries fuse the TP all-reduce, mHC input preparation (#57643) and the MoE finalize (#58586); a fused small-batch WO-A with inverse RoPE and MXFP8 quant on SM100/SM103 (#58634); the MXFP8 wo_b GEMM fused with the sequence-parallel reduce-scatter (#57428); Engram wkv sharded across TP ranks (#58678) and Engram host tables shared across co-located DP replicas by default (#57651); encoder CUDA graphs for the vision tower (#56625); and SWA bounded replay that keeps the sliding-window KV out of prefix caching (#56227).
Fast restart: the new vllm preload CLI launches the weight-cache daemon that keeps post-quantized weights resident in GPU memory across engine restarts (#56680), now with data parallelism (#57386), MTP draft models (#57312), a /health endpoint (#58552) and a readiness wait (#58370). Experimental initialized-engine snapshots (vllm snapshot create/restore) use CRIU to restore a fully initialized TP1 engine (#51360).
Model Runner V2 and speculative decoding: draft-model speculative decoding (#43091) and custom logits processors (#56497) on Model Runner V2; the new LiLiCorr drafter (#57934); async scheduling for DFlash (#58065) with the context K/V precompute captured in the draft CUDA graph (#57632); DSpark adaptive verification for Gemma4 (#57263) and variable-length decode for Kimi-K3 (#52988); a DCP target with a non-DCP DSpark draft (#56723); and MoE memory now counted during MRV2 profiling, avoiding OOMs on WideEP deployments (#57270, #58411).
Large scale serving: MoonEP balanced EP all2all backend via --all2all-backend moonep (#52101), prefill context parallelism with data parallelism (#57075), a low-SM multimem reduce-scatter for SM100/SM103 (#55072), DeepEPv2 with sequence parallelism (#57210) and EPLB with shared-expert overlap (#57236), a sharding-aware NCCL M2N weight-transfer backend for RL (#51520), and KV offloading back-pressure detection (#50045).
Scheduling controls: --max-num-active-seqs caps RUNNING admission independently of max_num_seqs (#56758), --long-prefill-token-threshold now adapts to the number of waiting prefills instead of chunking a lone request (#57951, #58459), the waiting queue was reworked so requests already holding KV blocks are scheduled first (#58947), and the KV connector + MTP deadlock under KV pressure was fixed (#57104).
HiSparse hardening: MTP verification rows resolved with a union residency kernel (#59235), MTP acceptance collapse under FULL graphs fixed (#59309), no GPU pages without host backing (#59036), a chunked-prefill preemption livelock fixed (#59494), KV cache sized from the groups HiSparse allocates (#59450), and host prefix publication and GPU prefix adoption fixes (#59007, #59282).
Security: per-request mm_processor_kwargs and media_io_kwargs are rejected unless --trust-request-mm-kwargs is set (#58830); prefix-cache extra keys are tagged by source so a LoRA name and a cache_salt can no longer collide (#51899), and the LoRA path is part of the block hash (#59335); stale multimodal receiver-cache entries can no longer replace fresh payloads (#57833).
Breaking changes: per-request multimodal kwargs gated (#58830); tokenizer_mode="slow" removed (#58545); --enable-mamba-fine-grained-prefix-cache renamed to --enable-mamba-shared-prefix-checkpoint (#57382); online quantization through quantization="fp8" replaced by the fp8_per_tensor shorthand (#53585) and Quark silent online quantization removed (#51800); the AllSpark INT8 W8A16 backend removed (#58001); --enforce-eager now also disables JIT kernel warmup (#58197); XPU graphs enabled by default with VLLM_XPU_ENABLE_XPU_GRAPH removed (#51600).

Release Artifacts

Python Wheels

| Platform | Install | |---|---| | PyPI (CUDA 13.0) | pip install vllm | | PyPI (CUDA 13.0, uv) | uv pip install vllm --torch-backend=auto | | ROCm | pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/0.31.0/rocm723 | | XPU | uv pip install vllm --extra-index-url https://wheels.vllm.ai/0.31.0/xpu --extra-index-url https://download.pytorch.org/whl/xpu --index-strategy unsafe-best-match |

Docker Images

| Platform | Docker Image | |---|---| | CUDA 13.0 (Default) | docker pull vllm/vllm-openai:v0.31.0 | | CUDA 12.9 | docker pull vllm/vllm-openai:v0.31.0-cu129 | | ROCm | docker pull vllm/vllm-openai-rocm:v0.31.0 | | CPU | docker pull vllm/vllm-openai-cpu:v0.31.0 | | XPU | docker pull vllm/vllm-openai-xpu:v0.31.0 |

Other Artifacts

Pre-built release artifacts are available in the Assets section at the bottom of this page, including:

Source distribution tarball
CUDA 12.9 Python wheels for x86_64 and arm64
CUDA 13.0 Python wheels for x86_64 and arm64
CPU Python wheels for x86_64, arm64, and macOS
XPU Python wheel for x86_64

Model Support

New model capabilities: DiffusionGemma structured generation mode with bounded single-token choices (#57250), MiMo V2 MXFP4 MoE, BF16 MoE router and DFlash drafts (#57784), Cohere2MoE auxiliary hidden states for EAGLE3/DFlash drafters (#49819), GLM-5.2-MXFP4 on the ROCm DeepSeek-V3.2 path (#51915), AMD-Quark mixed-precision DeepSeek-V4.1-Flash-MXFP4 (#57071) and GLM-5.3-Flash Quark MXFP4 (#56176) checkpoints, and a built-in granite_thinking_parser for Granite 4.2 (#55957).
DeepSeek-V4.1-Flash: FlashMLA mega attention with the NVFP4 compressed KV cache as the SM100 default (#56935), DeepGEMM sparse MQA logits in the indexer (#56254), Mega-Gate (#56266), fused TP all-reduce + mHC input preparation (#57643) with the MoE finalize folded in (#58586), fused small-batch WO-A (#58634), MXFP8 wo_b GEMM + reduce-scatter (#57428), overlapped mHC coefficients for small TP batches (#57603) limited to FULL CUDA graphs (#57874), Engram wkv sharded across TP (#58678), serialized Engram lookups with huge-page host tables (#56926), Engram tables shared across DP replicas by default (#57651, #57914, #59068), native shared-expert MegaMoE fusion without padding (#56568, #57204), faster MegaMoE staging and NVFP4 cache gathers (#57604), the fused query RMSNorm + MXFP8 path restored (#57679), KV-only DSpark context insertion (#56441), vision encoder CUDA graphs (#56625, #58499), SWA bounded replay (#56227), causal image SWA restored to match the reference (#57152), updated reasoning effort mappings (#58316), and startup fixes for NaN-scored candidate blocks (#57454), DeepSelect sentinels (#58215), DSpark non-causal attention on FlashInfer (#57432), runtime JIT of offset candidate buffers (#57667) and imports without Triton (#57654).
DeepSeek V4: FlashInfer sparse MLA with fused inverse RoPE + FP8 quant (#58621), stacked DSpark context WKV projections (#54674), fused MoE expert distribution computed from the EP group (#57465), FIM completion via suffix (#44229), missing string= in tool calls parsed (#56271), request tools attached to an existing system message (#51856), image block spacing preserved (#56882), and DSpark width separated from MTP stage validation (#54631).
GLM-5.3-Flash: opt-in FlashAttention and FlashMLA sparse backends on SM90 (#55385), NoPE sparse MLA on the FlashInfer SM120 backend (#55277), cooperative top-k for small decode batches (#57327), indexer decode workspace sized by pooled length (3 GiB saved, #57701), metadata ops 1.6-4.8x faster (#58450), fused kpool tail slot mapping (#57534), kpool top-k through the shared dispatcher (#57546), lower sparse MLA preparation overhead (#57458), no D2H sync in the SM90 sparse MLA plan under async scheduling (#58684), FlashKDA keeping the recurrent state in FP32 for long prefills (#58846), and correctness fixes for kpool corruption with speculative decoding (#58454), SM90 index_kpool mismatch (#58704), kpool tail strides (#57477), 500k-token prompts (#57317), dense MLP layers under sequence parallelism (#58061), indexer top-k backend selection (#58594) and varlen paged MQA launches (#55270).
Qwen3.8-Flash-Next (Qwen4Exp): FP8 main KV cache on the QSA path (#55557), FP8 TP with FlashInfer TRTLLM MoE (#55867), SM90 QSA tuning (#57273), fused HC down projection + SiLU (#58957), lower PLE metadata overhead (#58114), QSA indexer workspace fragmentation fixed (#57105), profiling KV cache released (#58961), pinned PLE prefetch ids kept out of the CUDA graph pool (#58489), and indexed expert-mapping lookups saving about 25 s of weight loading on DGX Spark (#58720).
Kimi K3 and MiniMax-M3: Kimi-K3 vision patch embedder as a GEMM (#58527), fused KimiViT QK RoPE (up to 29x, #58651), routed expert quantization (#57430), reasoning parser (#57098) and reasoning token counting (#58372) fixes, DSpark context KV pointers refreshed after re-binding (#58814), stateless first chunks no longer classified as decodes (#51483), and Mamba block estimates that no longer stall admission on external prefix hits (#57050); MiniMax-M3 encoder CUDA graphs (#58673), Conv3dLayer patch embedding (about 62x, #58512), triton_mrope in the vision tower (#58526), fused MiniMax2 routing with non-unit scaling (#58880), and processor fixes (#58460, #59613).
DiffusionGemma: one-pass sampler statistics kernel (#58226), diffusion_constrained reads over logprob_token_ids (about 25% faster, #58216), fewer logit rows for prefill-only batches (#57416), logprob_token_ids support (#57417), and fixes for concurrent logprobs (#57414), eager fallback dtype (#57462), multimodal inputs (#57589), quantized LM heads (#48521) and CPU execution (#58964).
Multimodal: Triton mm_input_norm kernel (#56798, #56711), raw pixels kept through the DP-sharded ViT path (#56872), Qwen2.5-VL video fps honored for temporal M-RoPE (#47736), Whisper and Qwen2-Audio clips longer than 30s (#57769, #56912), Mistral3 placeholder grid (#53758), Idefics3 unsplit patches (#48760), Ovis2.5 tokens (#52623), Aria expert weights (#57487), MiMo-V2.5 fused FP8 qkv_proj sharding (#57508), Gemma4 AutoWeightsLoader (#55911) and buffer scalars (#54213), Gemma4 FP8 KV with FA4 at head dim 512 (#53175), Laguna RoPE (#57189), Mistral-Large-3 accuracy regression (#57563), malformed EXIF (#56527, #57234), JinaVL labels (#57347), Sarvam MLA routing with FP32 router logits (#56034), fused CohereASR attention scores (#55190), and fused DFlash2 grouped convolution (#55960).
LoRA: Nemotron VL language models (#56231), ModernBert (#57148), VoyageQwen3 embeddings (#57708), RoBERTa sequence classification (#58884), and modules_to_save sequence-classification heads (#53555) with per-adapter num_labels (#57766).

Engine Core

Model Runner V2: draft-model speculative decoding (#43091), custom logits processors (#56497) validated at admission (#57728), randomized dummy inputs (#58411), dummy tokens routed to MoE experts during profiling (#57270), FULL decode graphs for one-token prompt tails (#58400), token-to-request mappings shared (#57102) and Mamba/GDN metadata reused across KV cache groups (#58762), encoder-only ViT CUDA graphs (#56922), weight offloader (#57834) and pooling model (#57737) released on shutdown, and fixes for multi-layer MTP KV in P/D (#55055), fast-prefill with LoRA (#56456), stale block-table writes from dummy draft steps (#56734), padded prompt tails in hybrid models (#58434), never-proposed draft slots (#58784), auto-fit max_model_len (#58149) and intermediate_tensors during capture (#57745).
Speculative decoding: LiLiCorr drafter (#57934), DFlash async scheduling (#58065) and context K/V in the draft CUDA graph (#57632), Gemma4 DSpark adaptive verification (#57263), Kimi-K3 variable-length adaptive verification (#52988), CPU-GPU sync removed for heterogeneous vocabularies (#57396), Triton recompiles avoided in the acceptance estimator (#57107), and fixes for EAGLE/dense drafts with EP (#56930), DFlash/DSpark profiling batches (#56448), GLM MTP head memory (#55442), prompt embeddings with drafts (#57356), and TritonMLA causal multi-token decode (#51065).
Scheduler: --max-num-active-seqs (#56758), adaptive --long-prefill-token-threshold (#57951, #58459), skipped_waiting replaced by a KV-holding waiting queue (#58947), atomic admission of n > 1 requests (#53936), KV connector + MTP deadlock (#57104), a throughput cliff when max_num_seqs is not a multiple of 8 (#57355), streaming continuations keeping logprobs and refreshing max tokens (#57447, #57676), a resumable request + async scheduling race (#58259), and a non-blocking structured-output grammar poll (#55931).
Prefix caching and hybrid models: extra keys tagged by source (#51899) and LoRA paths hashed (#59335), --enable-mamba-shared-prefix-checkpoint (#57382), prompt-tail hits with MTP restored (#58368), prompt-end checkpoints kept under sparse retention (#59146), align-mode checkpoint reservation (#59175), stateless GDN first chunks (#51565), MTP draft KV cache groups annotated on the hybrid grouping path (#55390), a generalized prefill checkpoint builder (#57783), batched Mamba2 prefill state saves without GPU-CPU syncs (#49371), skip_reading_prefix_cache honored for connector hits (#57269), incremental multimodal block hashing (#51694), a KV block size every attention backend supports (#49845) with clearer errors (#58557), and CacheConfig.effective_attention_block_size for DCP (#56538).
Startup and memory: parallel Triton warmup compilation (#58582), JIT warmup disabled under --enforce-eager (#58197) unless fault tolerance is on (#58593), DeepGEMM warmup reusing the MoE workspace (#57268), allocator fragmentation no longer shrinking the KV cache during profiling (#58430), sparse prefill buffers reserved before KV sizing (#57575), stale FlashMLA workspace views released (#56902), DeepGEMM FP8 workspace halved (#53914), shared Marlin/Humming workspaces (#57421), FlashInfer BF16 MoE weights converted in place (#54699), UniProc startup threads bounded by the CPU quota (#58946), and runtime threads set before profiling (#55891).