[denn-gubsky]

Recently I upgraded my TrueNAS box with Ryzen 7 8900 APU + 96GB DDR5. This config runs Ollama + loomcycle (my agentic Go runtime) + loomboard (the agentic UI), all self-hosted. I tired several models and Ollama configurations. For me is important to fit the whole model in GPU and run multiple agents+tool in parallel (see the blog for details: https://loomcycle.dev/blog/local-llms-on-truenas-and-the-fro...). Gemma4 is fast, but hallucinating a lot, especially when using tools. My current favorite is qwen3.6:27b. This is smart and reliable model, which can run tools in agentic configuration, do long researches, generate code, formulas and diagrams. On my hardware the qwen3.6 speed is about 9-13 tok/s, which is not high, but acceptable. The most tricky part is context size balancing for multiple model instances in limited memory. Ollama splits the context memory between model instances and may fail to run if agentic runtime allocates larger context than size than it is available in the context storage.