llama.cpp Release b10853 Adds Recurrent-State Rollback Support for Kimi-K3
Release b10853 of llama.cpp introduces support for Kimi-K3 recurrent-state rollback via Pull Request #28466. This allows the inference engine to restore previous internal recurrent states during stateful architecture operations. Recurrent-state rollback support is crucial for efficient speculative decoding and state management in modern hybrid or linear-attention models like Kimi-K3. Without state rollback support, speculative decoding steps would require costly full-state serialization to host memory, degrading inference throughput. The update specifically integrates Kimi-K3 into llama.cpp's recurrent-state rollback pipeline (#28466). It comes bundled with automated pre-built binaries across multiple operating systems and backends, including Windows, Linux, macOS, Android, CUDA, Vulkan, and SYCL.
## BACKGROUND
llama.cpp is a popular open-source C/C++ framework designed for lightweight, high-performance LLM inference across diverse hardware platforms. Kimi-K3 is a large language model developed by Moonshot AI that utilizes hybrid recurrent and linear attention mechanisms. Models with recurrent attention states rely on persistent internal state vectors, requiring efficient state rollback functionality to reject invalid draft tokens during speculative decoding without recalculating the entire sequence context.