Hardware and settings

12GB 3060 (omarchy, main node)

• GPU: NVIDIA RTX 3060, 12 GB
• CPU: Intel Core i5-10600 (6 cores, 12 threads)
• RAM: 77 GB
• OS: Arch Linux (Omarchy). Harnesses run in an incus container on the same host.

24GB M4 Mac Mini

• Apple M4, 24 GB unified memory
• LM Studio (MLX and GGUF) for Mac-sized models

Orange Pi 5 Plus 16 GB (RK3588)

• Rockchip RK3588: 4x Cortex-A76 + 4x Cortex-A55, Mali-G610 GPU, 6 TOPS NPU
• 16 GB LPDDR4X, shared by the CPU, GPU and NPU
• Engines: rkllama on the NPU (RKLLM models), llama.cpp on Vulkan or the CPU (GGUF)
• Builds here use the Pi builder: a small step-by-step harness with checkpoint steers, sized for 2B to 9B models. Its engine speed results are listed on the results page.

Engines

• Strata: a mixture-of-experts engine that streams experts from RAM and disk, so a model bigger than 12 GB of VRAM can run on the 3060 (Qwen3.8 Flash Next IQ3_XXS, Swift 1.5, the Coder).
• llama.cpp: dense and MoE GGUF models that fit (Bonsai 2 27B through PrismML's fork, Qwen3.6-35B-A3B, Ornith).
• LM Studio / MLX on the Mac mini.

Settings

Each model uses its card's recommended sampling preset. Thinking budget, context window and max output are recorded on every result page. The default for the pilot is medium thinking with a 3072-token budget and 7168 max output tokens.

Test machine

The checklist runs in headless Chromium on omarchy, pinned to two CPU cores and kept off the NVIDIA GPU, so it never competes with a model run.