AI & Local Models
KV Cache Quantization in llama.cpp for Consumer VRAM
llama.cpp KV cache quantization lets 8B models run 32kâ64k context on 8â16 GB cards. The math, the -fa prerequisite, and the flags.
llama.cpp KV cache quantization lets 8B models run 32kâ64k context on 8â16 GB cards. The math, the -fa prerequisite, and the flags.
Configure local coding models in VS Code with Ollama and Continue YAML, verify the backend, understand privacy limits, and compare tools honestly.
Build local PDF Q&A with current LangChain packages, labeled source chunks, validated citation IDs, retrieval tests, and honest hallucination limits.
Compare Faster-Whisper and whisper.cpp with current installation commands, built-in VAD options, hardware backends, and a repeatable audio test plan.
Plan a private CPU-based Ollama server with current DigitalOcean pricing, realistic memory limits, SSH-tunneled access, and repeatable measurements.