llama.cpp Adds Support for GLM-5.3-Flash (GLM5-Next) Architecture
llama.cpp has officially merged support (PR #27773) for the GLM-5.3-Flash (GLM5-Next) model architecture. This change enables users to convert, quantize, and run GLM-5.3-Flash models locally using the llama.cpp engine. GLM-5.3-Flash introduces a hybrid attention mechanism and sparse Mixture-of-Experts design optimized for high-efficiency agentic and long-context workloads. Bringing this architecture to llama.cpp expands the ecosystem of open-weight models playable on consumer-grade hardware. The GLM-5.3-Flash architecture utilizes a Mixture-of-Experts backbone with 320B total parameters and 18B active parameters, alongside Manifold-Constrained Hyper-Connections (mHC). The PR adds the tensor operations and graph execution support required to run quantized GGUF versions of this model family.
## BACKGROUND
llama.cpp is a widely used C/C++ framework designed for low-latency, local LLM inference across diverse hardware platforms. GLM-5.3-Flash (GLM5-Next) is a open-weight model family featuring hybrid sparse-linear attention built to reduce serving costs while maintaining long-context capabilities.