A practical local setup for using Hermes with modest hardware
can run locally on a Ryzen 9 3900 processor, 64GB of memory, and an RTX 4060 graphics card with 8GB of video memory. The setup uses the llama.cpp server, sends many model layers to the graphics card, uses compressed cache settings, and allows a very long . It reaches about 22 .
The model is only acceptable for complex coding, so Composer2.5 in Cursor and /Pro in VS Code are better choices for heavier programming work. Qwen is used for light coding, writing, and research, with Brave search connected inside Hermes. Tailscale makes Hermes and Open WebUI reachable from a phone and laptop.
integration is still a next step. For people without a large hardware budget, this kind of setup can reduce the need for s for research, writing, and simple questions.
Key points
- A 64GB memory machine with an 8GB video memory graphics card can run locally.
- Hermes can be paired with Brave search for research and writing work.
- Tailscale can make Hermes and Open WebUI available from a phone or laptop.
- Complex coding may still need stronger tools such as Cursor or VS Code with other models.
- This setup may help replace some s for everyday research, writing, and simple questions.