AI Briefing#ggml
The latest AI and developer news about #ggml, with the original source and a short summary.
The latest AI and developer news about #ggml, with the original source and a short summary.
The release removes deprecated APIs and adds FP8 support, YaRN truncation controls, and performance improvements across CUDA, Metal, Vulkan, and other backends.
The release establishes strict semantic versioning rules for the C API and expands distribution channels to include Docker, Debian, and conda-forge.
The tool supports CLAP, MERT, and MuQ models with CLI, HTTP, and Python, Rust, and Node.js bindings.
kimodo.cpp, a C++/GGML implementation of the NVIDIA Kimodo motion generation model without PyTorch, has been released, simplifying local inference environments.
llama.cpp has improved prompt processing speed by up to 31% through vectorization using F16C intrinsics.
audio.cpp 0.4 adds Higgs Audio v3 TTS and Fish Audio S2 Pro among others, now supporting 35 model families with Q8 GGUF improving speed and VRAM.
A high-performance, multi-model speech recognition (ASR) library built on ggml has been released.
llama.cpp's ggml library has added Q2_0 quantization for CPU to support Ternary Bonsai models.
audio.cpp, a C++/GGML-based framework, has undergone a major update by adding music and SFX generation as well as source separation features.
CUDA backend synchronization optimizations and asynchronous copy functionality have been added to the ggml library.
audio.cpp, a ggml-based C++ audio inference framework, has been released, offering up to 5x faster speed compared to Python.
llama.cpp has fixed an issue where quantized KV cache did not work when using --sm tensor in multi-GPU environments.
NVIDIA's Parakeet STT model has been ported to run in a C++/ggml environment without Python, greatly improving performance and efficiency.
The llama.cpp project has released a unified `llama` binary and an official website (llama.app).
Ollama has switched from a GGML-based build to direct llama.cpp support.
A C++ port of Echo-TTS that supports efficient inference using GGML and ONNX Runtime has been released.
vibevoice.cpp, a ggml-based inference engine that can run Microsoft VibeVoice without Python, has been released.
Luce DFlash boosted Qwen3.6-27B throughput by up to 2x on a single RTX 3090.
An open weights model has been released that transcribes overlapping speech from multiple speakers using a single model.
llama.cpp's ggml added graph_reused to reduce CUDA's O(n) change checks.
GGML, the team behind llama.cpp, has joined Hugging Face to strengthen support for the local AI ecosystem.
Introduces the features and core concepts of ggml, a low-level C/C++ library optimized for Transformer inference.