Files
agentic-kvc/third_party/vllm/docs/features
Gahow Wang 445e491123 Add vLLM v0.18.1 source tree with KV transfer abort fix
third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:

  vllm/v1/core/sched/scheduler.py:
    Replace fatal assert with graceful skip when KV transfer callback
    arrives for an already-aborted request during PD disaggregated serving.

Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-05-22 00:30:38 +08:00
..

Features

Compatibility Matrix

The tables below show mutually exclusive features and the support on some hardware.

The symbols used have the following meanings:

  • ✅ = Full compatibility
  • 🟠 = Partial compatibility
  • ❌ = No compatibility
  • ❔ = Unknown or TBD

!!! note Check the ❌ or 🟠 with links to see tracking issue for unsupported feature/hardware combination.

Feature x Feature

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Feature CP APC LoRA SD CUDA graph pooling enc-dec logP prmpt logP async output multi-step mm best-of beam-search prompt-embeds
CP ✅
APC ✅ ✅
LoRA ✅ ✅ ✅
SD ✅ ✅ ❌ ✅
CUDA graph ✅ ✅ ✅ ✅ ✅
pooling 🟠* 🟠* ✅ ❌ ✅ ✅
enc-dec ❌ ❌ ❌ ❌ ✅ ✅ ✅
logP ✅ ✅ ✅ ✅ ✅ ❌ ✅ ✅
prmpt logP ✅ ✅ ✅ ✅ ✅ ❌ ✅ ✅ ✅
async output ✅ ✅ ✅ ❌ ✅ ❌ ❌ ✅ ✅ ✅
multi-step ❌ ✅ ❌ ❌ ✅ ❌ ❌ ✅ ✅ ✅ ✅
mm ✅ ✅ 🟠^ ❔ ✅ ✅ ✅ ✅ ✅ ✅ ❔ ✅
best-of ✅ ✅ ✅ ❌ ✅ ❌ ✅ ✅ ✅ ❔ ❌ ✅ ✅
beam-search ✅ ✅ ✅ ❌ ✅ ❌ ✅ ✅ ✅ ❔ ❌ ❔ ✅ ✅
prompt-embeds ✅ ✅ ✅ ❌ ✅ ❌ ❌ ✅ ❌ ❔ ❔ ❌ ❔ ❔ ✅

* Chunked prefill and prefix caching are only applicable to last-token or all pooling with causal attention.
^ LoRA is only applicable to the language backbone of multimodal models.

Feature x Hardware

Feature Volta Turing Ampere Ada Hopper CPU AMD Intel GPU
CP ❌ ✅ ✅ ✅ ✅ ✅ ✅ ✅
APC ❌ ✅ ✅ ✅ ✅ ✅ ✅ ✅
LoRA ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
SD ✅ ✅ ✅ ✅ ✅ ❌ ✅ ✅
CUDA graph ✅ ✅ ✅ ✅ ✅ ❌ ✅ ❌
pooling ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
enc-dec ✅ ✅ ✅ ✅ ✅ ✅ ❌ ✅
mm ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
prompt-embeds ✅ ✅ ✅ ✅ ✅ ✅ ❔ ✅
logP ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
prmpt logP ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
async output ✅ ✅ ✅ ✅ ✅ ❌ ❌ ✅
multi-step ✅ ✅ ✅ ✅ ✅ ❌ ✅ ✅
best-of ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅
beam-search ✅ ✅ ✅ ✅ ✅ ✅ ✅ ✅

!!! note For information on feature support on Google TPU, please refer to the TPU-Inference Recommended Models and Features documentation.