精选85vLLM(GitHub Releases)AI 编程与模型
vLLM v0.24.0:新增 MiniMax-M3,设备选择改用 device_ids
v0.24.0
推荐理由
vLLM 是 AI 推理核心依赖,本次设备选择变更(CUDA_VISIBLE_DEVICES 改为 device_ids)可能影响现有部署脚本,建议升级前检查配置。同时新增多个模型支持,值得关注。
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).
- DeepSeek-V4 keeps maturing: Following its debut, DeepSeek-V4 received another large optimization pass — a FlashInfer sparse index cache (2–4% TTFT) (#45863), prefill chunk-planning optimization (4% E2E throughput) (#45061), a cluster-cooperative topK kernel for low-latency (#43008), contiguous per-block KV allocations (#44577), TEP=16 for the block-FP8 shared expert (#46001), and native DSA indexer decode for next_n > 2 on SM100 (#45322). It is now enabled on SM120 alongside GLM-5.1 (#43477), with XPU (#44144, #44517, #45240) and ROCm (#44899, #45103, #45681) attention/MoE paths added.
- Model Runner V2 (MRv2) continues to expand: MRv2 now supports quantized models by default (#44446), enables GraniteMoE by default (#45461), and gained migration of Qwen + DeepSeek-V2 MoE models (#42667), DFlash speculative decoding (#44586), and more accurate FP32 Gumbel sampling (#45996).
- Streaming Parser Engine: A new streaming parser engine unifies tool-call/reasoning parsing across models, with parsers for Qwen3 (#45413), MiniMax-M2 (#45701), GLM-4.7/5.1/5.2 (#45915), and Nemotron V3 (#45755).
- Diffusion LLMs: Added DiffusionGemma (#45163), including a CPU path (#45690) and structured-output guardrails for diffusion decoders (#45468).
- WideEP / DeepEP v2: Integrated DeepEP v2 for expert parallelism (#41183), with follow-on robustness fixes (#46404, #46432).
- Rust frontend matures further: Added API-key authentication (#44321), CORS (#45753), /tokenize + /detokenize (#44222), /pause /resume /is_paused (#44499), /abort_requests (#44382), /get_world_size (#44801), thinking_token_budget (#46137), a Python bridge for Rust tool parsers (#44624), and many new parsers and validation paths.
- Device selection change: vLLM no longer sets CUDA_VISIBLE_DEVICES internally; a new device_ids argument is provided instead (#45026). On ROCm, a deprecation window for CUDA_VISIBLE_DEVICES has begun (#46636).
Model Support
- New models: MiniMax-M3 (#45381), DiffusionGemma (#45163) + Gemma Diffusion on CPU (#45690), Hierarchical Reasoning Model — Text / HrmTextForCausalLM (#43098), OpenMOSS (#44124).
- Gemma 4: Unified FlashAttention (FA4) across all layers + mm_prefix support (#42175); many parser/serving fixes — forced-JSON skip for required/named tool choice (#45795), parsing with thinking disabled (#45832), streaming reasoning-state init (#45852), reasoning rendering on assistant turns (#45867), offline-parser truncation/token-leak fix (#45553); legacy Gemma4 parsers replaced with an engine-based implementation (#45588).
- DeepSeek-V4: OOM fix (#44914), MTP projection prefixing (#44821), supported KV-cache dtypes (#44892).
- Qwen / multimodal: Qwen3-VL video loader (#44412), Qwen2-VL/Qwen2.5-VL processor-mapped video loader (#45555), Qwen3-VL multi-video processing optimization (#46026) and multi-video crash fix (#46305), Qwen3-Omni VIT cu_seqlens device fix (#44264), fused qk-rmsnorm-rope-gate for Qwen3.5 (#44176), Qwen3.5 EP weight-loading fix (#45002).
- ViT full CUDA graph: GLM-4.1V (#40576), DeepSeek-OCR dual-path (#43586), Kimi-VL (#41992), mllama4 (#40660), Lfm2VL encoder (#44930).
- Other model fixes: Llama4 weight loading (#45047) and streamed loading to avoid host-OOM (#44645), MiMo v2.x QKV TP sharding + FP4 (#45200), ColQwen3.5 retrieval correctness (#46108), EXAONE-4.5 vision encoder (#45073), MiDashengLM TP>1 audio-encoder crash (#44408), MiniCPM-o/V device-placement and image-size fixes (#43844, #42332, #44980, #45244), Cohere2 MoE weight loading + parser (#44747, #44907), Nemotron V3 reasoning-as-content (#39091), ColBERT AutoWeightsLoader + query/document embedding io processor (#44999, #45210).
- Kernels: GLM-5 TRT-LLM ragged MLA prefill dimensions (#43525), GLM-5 router GEMM (#46385).
Engine Core
- Model Runner V2: Quantized models by default (#44446), GraniteMoE default (#45461), Qwen/DSv2 MoE migration (#42667), DFlash (#44586), simplified async output handling (#45442), attention-group split on num_heads_q (#45564), LoRA warmup fix (#35536), more accurate FP32 Gumbel sampling (#45996), min_tokens off-by-one fix in the V2 GPU sampler (#46243), plus assorted model/config compatibility fixes (#45868).
- Speculative decoding: Dynamic SD (#32374); DFlash with FlashInfer (#43081), mixed KV page sizes (#45181), and Qwen3Next targets (#45319); EAGLE3 support for Qwen3 (#43132); reduced TP communication for large-vocab drafts (#39419); race fix in async accepted counts (#45100); EAGLE multimodal encoder cache fixes (#46315).
- KV cache & scheduler: KV-cache watermark to reduce preemptions (#44594), two-phase allocation for cross-group prefix-cache hits (#44409), Marconi-style admission policy for hybrid cache (#37898), prefix-cache retention for Mamba/linear attention (#45845), DS Mamba tail-copy for MTP align mode (#45473), reduced scheduler copy overhead (#45840).
- Attention: Re-enabled cross-layer KV cache layout for MLA via stride-aware kernels (#45111), MLA prefill FA4 fp8 output (#43050), FlexAttention custom mask mods made fully cudagraphable (#45232), triton diff-kv backend for MiMo (#41797), FlashMLA sparse accuracy fix (#36616).
- Weight loading & core: fastsafetensors ParallelLoader for weight loading (#40183), release of cached device memory under pressure on UMA GPUs (#45179), structured outputs for beam search (#35022), device_ids arg / no internal CUDA_VISIBLE_DEVICES (#45026), graceful fallback when numactl --membind is blocked (#45438), config-class registration before tokenizer init (#40299), async scheduling with prompt embeds for multimodal models (#45673).
Large Scale Serving & Distributed
- Expert parallel: DeepEP v2 integration (#41183) with token-bound and topk-index fixes (#46404, #46432); NIXL EP — DBO with NIXL EP (#45275), top-k index dtype query (#45298), NVFP4 post-receive quantization skip (#45606), elastic-EP communicator (#45013); reject NCCL-based EPLB with async EPLB (#44978).
- KV connectors / disaggregated serving: KV push from prefill to decode via NIXL (#35264); per-region KV transfer classification for mixed full-attn + MLA groups (#44583); Mooncake pipeline-parallel PD support (#44528), async lookup (#45659), compact chunk-hash zero-copy lookup (#45969), SWA-block skipping (#45444); P/D fixes with DP supervisor (#46628) and DSV4 disaggregation (#45831); removed P2pNcclConnector (#44854).
- KV offloading: Multi-tier async batched lookup (#44193), packed HMA KV-cache layout (#46205, gated #46252), parallel-agnostic fs-tier cache (#44733), offloading-manager stats (#35669) and labeled/CPU-usage metrics (#45957, #45737), self-describing KV events (#43468), non-blocking idle flush (#45595), and numerous correctness/race fixes (#44784, #45823, #46231, #46278).
- Distributed core: Prefill step cadence for better non-PD DP balancing (#44558), KV-event map encoding (#42892), one-shot fused all-reduce PDL NaN fix (#45448).
Hardware & Performance
- NVIDIA / kernels: SM90 CUTLASS FP8 mm odd-M support via swap_ab (180–290% kernel speedup) (#44572), tuned fused_moe FP8 for Qwen3-Next-80B on H100 (+25%) (#44830), native DSA indexer decode on SM100 (#45322), cluster-cooperative topK for DeepSeek low-latency (#43008), PDL support for DeepGEMM (#46006), FlashInfer cutedsl NVFP4 GEMM (#42235) and cute-dsl MXFP8 linear kernel (#46393), new Helion kernels for FP8/RMSNorm quant (#36902, #33790, #36895, #34432).
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