vllm-project/vllm

[Feature]: Extract KV-Cache update from all attention backends

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#32335 opened on Jan 14, 2026

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 (51 comments) (0 reactions) (9 assignees)Python (80,034 stars) (16,816 forks)batch import
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Description

🚀 The feature, motivation and pitch

Similar to how https://github.com/vllm-project/vllm/pull/25954 extracts it from FlashAttn. Ideally, we want to cover all backends with kv-cache update from v1/attention/backends.

Backends:

  • FlashAttention
  • FlashInfer
  • AiterFlashAttention (in progress)
  • RocmAiterUnifiedAttention
  • RocmAttention
  • TritonAttention
  • FlashAttentionDiffKV
  • FlexAttention
  • TreeAttention

MLA Backends:

  • FlashAttnMLA
  • FlashInferMLA
  • FlashMLASparse
  • FlashMLA
  • AiterMLA
  • ROCMAiterMLASparse
  • CutlassMLA
  • TritonMLA

After all backends are supported, we can remove slot_mapping from attention metadata.

Alternatives

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Additional context

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Contributor guide

Tech stack
pythonpytorchcpp
Domain
backendperformanceai
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
5
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
vllm attention backendsKV cache optimizationCUDA programmingv1/attention module
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
10
Research direction
Review PR #25954 which demonstrates the extraction pattern for FlashAttn. Examine the existing completed backends (e.g., FlashInfer, TritonAttention) in `v1/attention/backends` to understand the structure. The AiterFlashAttention backend is in progress; coordinate with the current assignees. The goal is to implement the KV cache update extraction for the remaining backends and eventually remove `slot mapping` from attention metadata.