The b12180 release of ggml-org/llama.cpp added the Kimi-K3.1-Pro text model. This repository is an LLM inference project written in C and C++. The core of this change is the addition of support related to the attention configuration needed to handle that text model. The change is recorded in the b12180 release notes on GitHub.
According to the release notes, the full attention layers were replaced with DSA. Lightning indexers were layered onto 24 of the 93 layers, while the remaining linear attention layers and the mixture-of-experts structure were kept. So this was not a change that converted every layer in the same way: it applied lightning indexers to some layers and left the other configurations untouched. For validation, it explains that 38 tensors were compared exactly on an 8-layer shard basis. The official full name of DSA, and what the comparison was made against, do not appear in the provided information.
What this release information confirms is limited to the model addition, the layer configuration changes, and the tensor comparison validation. It explains that 38 tensors were compared exactly, but does not say what they were compared against or how the full 93 layers were validated. There are also no figures for performance, execution speed, or memory usage. Therefore, from this record alone, it cannot be concluded that inference efficiency has improved; the confirmable change is limited to Kimi-K3.1-Pro text model support and the described configuration changes.