# vLLM v0.31.0 — Release & Upgrade Intelligence
- **Product:** vLLM (https://vllm.ai)
- **Version:** v0.31.0
- **Released:** Oct 05, 2026
- **Impact Score:** 7/10
- **Breaking Changes:** Source flagged
- **Canonical Analysis:** https://changelogs.us/vllm/updates/v0.31.0/

## Executive Summary (TL;DR)
vLLM v0.31.0. Source highlight: This release features 717 commits from 307 contributors (96 new)!

## Breaking Changes & Deprecations
- 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).
- Breaking Changes & Deprecations * Per-request `mm_processor_kwargs` and `media_io_kwargs` now return an error unless the server is started with `--trust-request-mm-kwargs`; server-level `--mm-processor-kwargs` / `--media-io-kwargs` and offline `LLM` are unchanged (#58830). * `tokenizer_mode="slow"` was removed; it already behaved like `"hf"` under Transformers v5 (#58545).

## New Features
- **KV connectors**: NIXL pipeline-parallel push prefill for attention-HMA (#50494) and packed MLA layouts (#50499), transport-failure metrics split from KV expiry (#55854), dead peer state released without waiting for TTL (#50047), expired leases reaped behind a heartbeated head (#58292), push completion restored (#58188), D-side activity recorded (#52245); Mooncake `CUSTOM_MEM_POOL` (#49300), request-level load failures under HMA (#56855, #57174) and bootstrap retries (#58919); MoRIIO hybrid Mam
- Prefix-cache block hashes tag extra keys by source (#51899) and include the LoRA path (#59335); multimodal hash input is framed (#54283) and incremental block hashing covers every overlapping feature (#51694).

## Improvements
- **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 r

## Bug Fixes
- **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).
- **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), ser
- **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
- **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), `Conv3dLay

## Upgrade Command
```bash
python -m pip install 'vllm==0.31.0'
```