Docker Images and Containers
MetalGlot runs its local AI translation backend in Docker. Before you can translate anything, you need to download the right CPU or CUDA image, create a container from that image, and start it from the app.
Available Docker Images
Section titled “Available Docker Images”Open Setup Container from the home page toolbar to see the available image variants.
| Variant | Best for | Approximate compressed download size |
|---|---|---|
| CPU only | Systems without a compatible NVIDIA GPU | 1013 MB |
| CUDA Legacy 10xx Pascal | NVIDIA 10-series GPUs | 4.31 GB |
| CUDA Mainstream 20xx/30xx/40xx/A100 | Most current NVIDIA desktop GPUs and A100-class systems | 4.42 GB |
| CUDA Next-gen 50xx/B200 | Newer NVIDIA 50-series and next-generation compatible systems | 7.12 GB |
If you are not sure whether a CUDA option matches your GPU generation, use the CPU image instead of forcing the wrong CUDA variant.
If you want the simplest and safest starting point, begin with the CPU image. Choose a CUDA image when you know your NVIDIA generation matches the listed variant.
How To Download A Docker Image
Section titled “How To Download A Docker Image”- Open Setup Container.
- Review the available image variants.
- Choose Download for the variant that matches your hardware.
- Watch the Progress monitor until the download completes.
Docker image downloads and model downloads are separate. You download the container image first, then you download translation models later from the model manager.
How To Create A Container
Section titled “How To Create A Container”Once an image is present, choose Create container for that image.
During container creation, MetalGlot asks you to configure the model folder and optional resource settings.
Choose A Model Folder
Section titled “Choose A Model Folder”This is the most important container setting.
The folder you choose becomes that container’s model library from the app’s point of view. When you later open Manage AI models, MetalGlot shows and uses the folder that belongs to the currently selected container.
That folder is where the GGUF models and vision models for that container are stored.
That means every container can have its own download folder.
| Container purpose | Example host folder |
|---|---|
| CPU setup | D:\MetalGlot\models-cpu |
| GPU setup | D:\MetalGlot\models-gpu |
| Experimental setup | D:\MetalGlot\models-test |
Using separate folders keeps lightweight CPU downloads separate from larger GPU-focused model libraries.
Configure CPU Resources
Section titled “Configure CPU Resources”MetalGlot offers two CPU modes:
- Use all CPU resources.
- Specify CPU threads.
Start with the default unless you have a reason to limit CPU usage on a shared workstation.
Configure GPU Resources
Section titled “Configure GPU Resources”CUDA containers also expose GPU controls:
- Use entire GPU resources.
- Advanced: specify GPU layers.
When advanced GPU tuning is available, MetalGlot shows detected GPU memory and an estimated layer recommendation for the currently selected model family. Use that estimate as a starting point, not as a strict rule.
Starting, Stopping, And Switching Containers
Section titled “Starting, Stopping, And Switching Containers”Back on the home page toolbar, you can:
- Select a container from the container picker.
- Start the selected container.
- Stop the running container.
- Delete a container you no longer need.
MetalGlot expects one active translation container at a time. If another MetalGlot container is already running, stop it before starting a different one.
How Container Selection Affects Model Management
Section titled “How Container Selection Affects Model Management”The selected container controls:
- Which model folder is shown in Manage AI models.
- Which downloaded models are visible from the app.
- Which local backend is currently serving translation requests.
If you switch containers, you are also switching to that container’s model folder and available model library.
Docker Image Download Behavior
Section titled “Docker Image Download Behavior”Docker image downloads show progress in the Docker setup dialog.
- You can cancel an in-progress image download.
- After cancellation, you can restart the image download later.
- Docker image downloads do not use the same pause and resume workflow as GGUF model downloads.
Troubleshooting Basics
Section titled “Troubleshooting Basics”- If MetalGlot says Docker is not detected, install Docker Desktop first.
- If Docker is detected but not running, start Docker Desktop and wait for it to finish launching.
- If a container exists but will not start, make sure another MetalGlot container is not already running.
- If model downloads are unavailable, confirm that the selected container was created with a valid model folder.