SkillFishOS can run local LLMs on the BC-250's integrated GPU, accelerated in Vulkan — nothing leaves the machine.

• Unsloth Studio as the engine, accelerated via Vulkan on the Cyan Skillfish GPU. It is a single native service that provides both the chat interface and an OpenAI-compatible API, listening on 127.0.0.1:8888.
• A one-click AI panel (skillfish-ai-panel) that starts and stops it.
• The Remote Manager proxies it at /unsloth, so the same engine is reachable from another machine on the LAN without opening a second port.

It used to be Ollama plus OpenWebUI in three Docker containers with a ~6.5 GB custom image. That is gone since 26.08: one service, no Docker.

Why Vulkan matters here: measured on this hardware, the same model runs at about 210 tokens/s on the GPU against 41 on the CPU. It is not a rounding difference, it is the whole reason on-device AI is usable on this board.

• A first-run wizard installs the stack and lets you pick a model from a curated list of 30+ options that fit the hardware (≤14B).
• Live readout of CPU / GPU / VRAM / RAM.
• A slider to grow the shared memory (GTT) available to the model — see Memory VRAM and GTT.
• Turn the engine off with one click to free the GPU and memory for gaming.

• Bigger models need more memory: raise the GTT budget (and/or the UMA VRAM) before loading a large model.
• The GPU governor's idle behaviour means the card drops to 350 MHz between prompts; under inference it ramps up. For sustained throughput you can pick Performance GPU Governor and Tuning — though for pure compute the 2230 MHz point can help (with adequate voltage/cooling), the shipped safe cap is 2200 MHz.
• Unlocking Compute Units (40-CU) roughly ×ばつ's the GPU's compute throughput.

Nothing here phones home — the models and the chat run entirely on your BC-250.