llama.cpp

Discover how PFlash achieves a 10x speedup in llama.cpp prefill, the latest Ollama performance updates for Qwen models, and a guide to deploying fine-tuned Llama 3.2 on Android.

Local LLMs often struggle with structured JSON output compared to managed APIs. This guide explores the three main failure patterns and provides code-based solutions using GBNF grammar, JSON Schema, and two-stage generation.

Alibaba's Qwen 3.6 27B model has launched, featuring flagship-level coding power and immediate GGUF support via Unsloth. This release, alongside new Rust-based multimodal tools, marks a major shift for local LLM deployment on consumer hardware.

A deep dive into the latest breakthroughs for Google's Gemma 4, including critical memory optimizations in llama.cpp, Ollama performance on RTX 3090, and ultra-efficient NPU deployments.

A comprehensive guide on managing Gemma 4 models, focusing on TRL v1.0 fine-tuning, llama.cpp tokenizer fixes, and strategies to overcome the significant KV cache VRAM demands on RTX hardware.

A technical deep dive into bridging the gap between NVIDIA's Blackwell architecture and Apple's M2 Ultra using llama.cpp and 10GbE for massive 200B+ parameter model inference.

The integration of GGML and llama.cpp into Hugging Face marks a pivotal moment for Local AI, enabling seamless transitions between open-source research and consumer-grade hardware deployment.

An in-depth investigation into why Claude Code crashes when pointed at local LLM servers like llama.cpp and how to fix it with a Python proxy.

Explore the latest updates in llama.cpp model management, including direct Hugging Face integration, enhanced GGUF support, and how to optimize your local LLM workflow compared to managed services like n1n.ai.