llama.cpp
llama.cpp on Beyond Market Intelligence: a running collection of 5 stories we have gathered and hand-picked because they are worth your time. Every post here touches on llama.cpp in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around llama.cpp, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Speed Up LLM Inference with DSpark Speculative Decoding
Accelerate your local LLM generation speed with DSpark speculative decoding. This technique leverages your existing GPU to significantly boost performance, demonstrated here with Qwen3-8B, llama.cpp, and CUDA. DSpark intelligently predicts upcoming tokens, minimizing computation and maximizing throughput. Explore this transformative approach to AI inference and unlock greater efficiency. For a broader perspective on the shift toward local AI, see our article, "Apple's New Mac Line is Built Around Local AI." Discover how to harness this power today.
Meta returns to open source with Muse Glimmer, an Apache 2.0 licensed 30B parameter AI model optimized for agents — available now
Meta’s return to open source with Muse Glimmer marks a significant shift in the AI landscape. This 30-billion-parameter model, licensed under the permissive Apache 2.0, is specifically optimized for autonomous AI agents and designed to run directly on consumer hardware like Macs and PCs. Unlike previous Meta releases, Glimmer offers unrestricted commercial use and redistribution. The model's ability to operate locally, without cloud dependency, enhances data privacy and reduces costs, as demonstrated by its efficient performance on just 24GB of VRAM.
No cloud, no GPUs, no problem: Liquid AI's new model LFM2.5-2.6B brings powerful AI agents to devices as small as a Raspberry Pi
Liquid AI has unveiled LFM2.5-2.6B, a new open-weight language model designed to bring powerful AI agents to devices as small as a Raspberry Pi – a significant step toward accessible edge AI. This model, boasting 2.6 billion parameters and a 128,000-token context window, runs entirely on local hardware without cloud inference or GPUs, ideal for high-volume tasks like automation and connectivity-limited environments. Explore how this innovative solution transforms data management and expands possibilities for enterprises, as highlighted in our recent coverage of Qwen 3.8-Max.
ARPL — runtime ISA/topology detection for llama.cpp on ARM (built for Snapdragon 8 Elite) [r]
ARPL delivers a significant advancement for llama.cpp on ARM devices, particularly Snapdragon 8 Elite platforms. This open-source project dynamically detects runtime ISA extensions (SDOT, I8MM, SME2) and core topology, automatically configuring llama.cpp for optimal performance—eliminating manual tuning and per-device builds. The included Android reference app showcases this capability, demonstrating a tangible improvement in efficiency.
Run the Mythos Enhanced Coding Model Locally with llama.cpp and Pi
Unlock powerful local coding workflows with the Qwythos-9B-Claude-Mythos-5-1M model. Run this enhanced coding model locally using llama.cpp, then seamlessly integrate it with the Pi coding agent. This configuration enables fast, responsive coding directly on your machine, leveraging MTP speculative decoding and an OpenAI-compatible API. Explore a future-focused solution that empowers developers to build and iterate with unprecedented speed and accessibility. Interested in expanding your AI skillset? Check out our "5 Free Courses to Go From AI Beginner to Practitioner" for a comprehensive learning path.