Hi again! It's been a while since my last llamaMan article, and honestly the project outpaced my ability to write about it. The last update stopped at 1.2.2; we're now at 2.2.2, and the gap in between is... a lot. So instead of a release-by-release dump - no, wait. This time it *is* a release-by-release tour, but only the releases with something big in them, newest first. The patch-level fixes and wording tweaks I'll quietly skip.

llamaMan turns a single llama.cpp manager into a multi-node cluster - pool your spare PCs into one load-balanced, Ollama-compatible inference endpoint. Here's everything new across the 1.x line.

Exploring the Llamaman implementation and deployment of TurboQuant after 2am.

LlamaMan is a self-hosted web UI for managing llama.cpp instances. Check out what's new in version 0.8.6

Ollama was too slow and apparently nobody had built a proper UI for managing llama.cpp instances in Docker. So I did. LlamaMan gives you full control over GPU layer offload, real-time VRAM monitoring, one-click model launching from a preset, and an Ollama-compatible proxy. Having control over your own hardware shouldn't be a novel concept in 2026.