llama.cpp Release b10155 Adds Support for MiMo-V2.5 Audio Input
The llama.cpp project has released version b10155, introducing native C++ support and a GGUF converter for the MiMo-V2.5 audio input model. This update enables the processing of RVQ-based (Residual Vector Quantization) audio models directly within the llama.cpp ecosystem. This release expands llama.cpp's capabilities into multimodal audio processing, allowing developers to run efficient, local audio-to-text or omnimodal models. It lowers the barrier for deploying advanced audio AI applications on consumer hardware. The update includes a dedicated GGUF converter for MiMo audio, a C++ implementation, and fixes for convolutional layers. The supported MiMo-V2.5 model relies on Residual Vector Quantization (RVQ) to compress and represent audio data.
## BACKGROUND
MiMo-V2.5 is an omnimodal model developed by Xiaomi that supports text, image, video, and audio understanding. Residual Vector Quantization (RVQ) is a technique that approximates high-dimensional vectors using a cascade of codebooks, which is highly effective for compressing audio signals. GGUF is a binary file format optimized for fast loading and saving of LLM weights, widely used in the llama.cpp ecosystem.