github llama.cpp · 3d ago · inference

llama.cpp b10935 adds LOG_JSON macro for structured logging

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The llama.cpp project released build b10935, which introduces the LOG_JSON macro to enable structured data logging. This change allows developers to fit log outputs into a JSON format for easier parsing and integration.

Added the LOG_JSON macro to the common logging infrastructure.
Included a demo implementation of LOG_JSON within the fit module.
Provided binaries for macOS (Apple Silicon and Intel), Linux (CPU, Vulkan, ROCm, OpenVINO, SYCL), Windows (CPU, CUDA 12/13, Vulkan, OpenVINO, SYCL, ROCm), Android, and iOS.

This update enhances the tooling available to developers by standardizing log output formats.

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github llama.cpp · 1h ago · 1 view Live

llama.cpp b10984 adds CUDA row-contiguous SUM_ROWS support

The llama.cpp project released version b10984, introducing CUDA support for row-contiguous SUM_ROWS operations. This update also organizes the code to include GGML_OP_MEAN for handling row-contiguous tensors via a shared kernel.

github llama.cpp · 2h ago · 1 view

llama.cpp b10985 restricts RPC hash-cache to weights

The llama.cpp project released build b10985, which modifies the RPC backend to limit hash-based caching exclusively to weight tensors. This change addresses an issue where activation data was unnecessarily hashed and stored, leading to excessive disk usage.

github llama.cpp · 3h ago · 4 views

llama.cpp b10982 adds Vulkan sparse Flash Attention support for DSV4/GLM

The llama.cpp project has released build b10982, which introduces support for sparse Flash Attention via the Vulkan backend. This update specifically targets DSV4 and GLM models, allowing them to leverage sparse attention mechanisms on compatible GPU hardware.

github llama.cpp · 4h ago · 2 views

llama.cpp b10981 fixes stateful decode for Gemma-4 and optimizes GPU MoE inference

The llama.cpp b10981 release addresses critical correctness issues in the OpenVINO backend's stateful decoding path, specifically fixing support for models like Gemma-4 that use per-layer head sizes. It also introduces optimizations for GPU Mixture of Experts (MoE) inference and improves performance through KV state relayouts.

github llama.cpp · 5h ago · 1 view

llama.cpp adds Metal FA kernels for MiniCPM3's HSK=96, HSV=64

The llama.cpp project has added Flash Attention (FA) kernel support for the specific configuration used by MiniCPM3 on Apple Silicon. This change addresses a crash where the `-fa auto` flag would abort due to a missing kernel instantiation for attention key length 96 and value length 64.