[KongchangAI]
ConceptV2架构 / Model Runner V2

Model Runner V2

The second-generation model execution engine for the vLLM framework, featuring a comprehensive redesign of the underlying scheduling logic, memory management, and batching strategy. It became the default runtime for all models starting with vLLM v0.29.0.

Timeline (last 90 days)

Oct 1

vLLM released release candidate v0.31.0rc3, with the core highlight being the introduction of Randomized Dummy Inputs support for Model Runner V2.

Unverified50%
Sep 24

v0.30.0 launches a new Model Runner V2, bringing EAGLE3-style draft generation into pipeline parallelism.

Unverified50%
Sep 15

In vLLM v0.29.0, Model Runner V2 officially became the default execution engine for all models.

Unverified50%
Sep 15

Teams using vLLM in production environments are advised to evaluate potential behavioral changes caused by the default engine switch before upgrading, and to validate throughput and latency metrics in a test environment.

Unverified50%
Sep 12

Model Runner V2 gains two capabilities in vLLM v0.28.0: E/P/D separation (Encode/Prefill/Decode disaggregated deployment) and weight offloading.

Unverified50%
Sep 11

Model Runner V2 (MRV2) capabilities are extended to non-generative workloads, supporting encoder-only attention, sequence pooling, BGE-M3 pooling, and multimodal execution on CPU.

Unverified50%

All Facts (6)

Source Articles