llama.cpp Server GUI
Posted: Sat Apr 18, 2026 5:02 am
A professional PyQt6-based graphical interface for managing llama.cpp server instances.
Features
Server Binary Selection: Browse and select your llama.cpp server binary
Model Selection: Easy selection of GGUF model files
Comprehensive Options: Configure host, port, context length, GPU layers, threads, batch size, and more
Start/Stop Controls: Simple buttons to start and stop the server
Real-time Logs: View server output and errors in real-time
Profile Management: Save and load different configurations for different models/use cases
Configuration Persistence: All settings are saved between sessions
System Tray Icon: Minimize to tray to keep the server running in the background
Auto-start: Option to automatically start the server when the GUI launches
Requirements
Python 3
PyQt6
llama.cpp server binary
Installation
Install PyQt6:
sudo apt install python3-pyqt6
Make sure you have llama.cpp compiled with the server binary
Usage
Run the application:
./llama_server_gui.py
Or:
python3 llama_server_gui.py
Quick Start
Select Server Binary: Click "Browse..." in the "Server Binary" section and navigate to your llama.cpp server binary (e.g., /home/xero110/dev/llama.cpp/build/bin/llama-server)
Select Model: Click "Browse..." in the "Model Selection" section and choose your GGUF model file
Configure Options: Adjust the server options as needed:
Host: IP address to bind to (default: 127.0.0.1)
Port: Port number (default: 8080)
Context Length: Maximum context size (default: 2048)
GPU Layers (ngl): Number of layers to offload to GPU (default: 33)
Threads: CPU threads to use (default: 8)
Batch Size: Batch size for processing (default: 512)
Additional Arguments: Any extra command-line arguments
Start Server: Click "Start Server"
Save Profile: Once you have a configuration you like, click "Save Profile" to save it for later use
Profile Management
Save Profile: Saves the current configuration with a custom name
Load Profile: Select a profile from the dropdown and click "Load" to load its settings (profiles also auto-load when selected from dropdown)
Delete Profile: Removes the selected profile
Auto-start: Check this option to automatically start the server when the GUI launches
The GUI now includes detailed logging in the log viewer at the bottom, showing when profiles are saved, loaded, and what settings are being applied.
System Tray
The application includes a system tray icon that allows you to:
Show/hide the main window
Start/stop the server from the tray menu
Quit the application
When you close the window while the server is running, you can choose to:
Minimize to tray (server keeps running)
Stop server and quit
Cancel the close operation
Configuration File
Settings are stored in ~/.llama_server_gui_config.json
Common Server Options Explained
Context Length (-c): Maximum number of tokens the model can process at once. Larger values use more RAM/VRAM.
GPU Layers (-ngl): Number of model layers to offload to GPU. Higher = faster but uses more VRAM. Set to -1 for all layers.
Threads (-t): Number of CPU threads for processing. Usually set to your CPU core count or less.
Batch Size (-b): Number of tokens processed in parallel. Larger = faster but uses more memory.
Host: Network interface to bind to. Use 127.0.0.1 for local-only access, or 0.0.0.0 to allow network access.
Port: Network port for the server API.
Tips
For RTX 4070 (8GB VRAM): Start with ngl=33 and adjust based on your model size
With 96GB RAM and i9 CPU: You can use high thread counts (16-24) and large context sizes
Create different profiles for different models (e.g., "Llama-3-8B", "Mistral-7B", etc.)
Use the system tray to keep the server running while working on other tasks
Troubleshooting
Server won't start:
Check that the binary path is correct and the file is executable
Verify the model path is correct
Check the logs for error messages
Out of memory errors:
Reduce context length
Reduce GPU layers (ngl)
Use a smaller model
Slow performance:
Increase GPU layers if you have VRAM available
Adjust thread count
Increase batch size (if you have memory available)
Features
Server Binary Selection: Browse and select your llama.cpp server binary
Model Selection: Easy selection of GGUF model files
Comprehensive Options: Configure host, port, context length, GPU layers, threads, batch size, and more
Start/Stop Controls: Simple buttons to start and stop the server
Real-time Logs: View server output and errors in real-time
Profile Management: Save and load different configurations for different models/use cases
Configuration Persistence: All settings are saved between sessions
System Tray Icon: Minimize to tray to keep the server running in the background
Auto-start: Option to automatically start the server when the GUI launches
Requirements
Python 3
PyQt6
llama.cpp server binary
Installation
Install PyQt6:
sudo apt install python3-pyqt6
Make sure you have llama.cpp compiled with the server binary
Usage
Run the application:
./llama_server_gui.py
Or:
python3 llama_server_gui.py
Quick Start
Select Server Binary: Click "Browse..." in the "Server Binary" section and navigate to your llama.cpp server binary (e.g., /home/xero110/dev/llama.cpp/build/bin/llama-server)
Select Model: Click "Browse..." in the "Model Selection" section and choose your GGUF model file
Configure Options: Adjust the server options as needed:
Host: IP address to bind to (default: 127.0.0.1)
Port: Port number (default: 8080)
Context Length: Maximum context size (default: 2048)
GPU Layers (ngl): Number of layers to offload to GPU (default: 33)
Threads: CPU threads to use (default: 8)
Batch Size: Batch size for processing (default: 512)
Additional Arguments: Any extra command-line arguments
Start Server: Click "Start Server"
Save Profile: Once you have a configuration you like, click "Save Profile" to save it for later use
Profile Management
Save Profile: Saves the current configuration with a custom name
Load Profile: Select a profile from the dropdown and click "Load" to load its settings (profiles also auto-load when selected from dropdown)
Delete Profile: Removes the selected profile
Auto-start: Check this option to automatically start the server when the GUI launches
The GUI now includes detailed logging in the log viewer at the bottom, showing when profiles are saved, loaded, and what settings are being applied.
System Tray
The application includes a system tray icon that allows you to:
Show/hide the main window
Start/stop the server from the tray menu
Quit the application
When you close the window while the server is running, you can choose to:
Minimize to tray (server keeps running)
Stop server and quit
Cancel the close operation
Configuration File
Settings are stored in ~/.llama_server_gui_config.json
Common Server Options Explained
Context Length (-c): Maximum number of tokens the model can process at once. Larger values use more RAM/VRAM.
GPU Layers (-ngl): Number of model layers to offload to GPU. Higher = faster but uses more VRAM. Set to -1 for all layers.
Threads (-t): Number of CPU threads for processing. Usually set to your CPU core count or less.
Batch Size (-b): Number of tokens processed in parallel. Larger = faster but uses more memory.
Host: Network interface to bind to. Use 127.0.0.1 for local-only access, or 0.0.0.0 to allow network access.
Port: Network port for the server API.
Tips
For RTX 4070 (8GB VRAM): Start with ngl=33 and adjust based on your model size
With 96GB RAM and i9 CPU: You can use high thread counts (16-24) and large context sizes
Create different profiles for different models (e.g., "Llama-3-8B", "Mistral-7B", etc.)
Use the system tray to keep the server running while working on other tasks
Troubleshooting
Server won't start:
Check that the binary path is correct and the file is executable
Verify the model path is correct
Check the logs for error messages
Out of memory errors:
Reduce context length
Reduce GPU layers (ngl)
Use a smaller model
Slow performance:
Increase GPU layers if you have VRAM available
Adjust thread count
Increase batch size (if you have memory available)