vLLM Implements K-EXAONE Configuration and RoPE Support
October 10, 2026
vLLM now supports K-EXAONE by restoring pre-2.0 configuration loading and applying Rotary Positional Embedding (RoPE) to the Multi-Token Prediction (MTP) layer. This enables optimized high-throughput serving for the K-EXAONE architecture.
HOW THIS AFFECTS YOU
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builderYou can serve K-EXAONE models with improved performance via vLLM's optimized kernels.
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researcherThe inclusion of MTP layer RoPE support facilitates more accurate evaluation of multi-token prediction architectures.