🧱 A Dockerfile describes how to build a container image.
It specifies things like:
OS / base image
Python / dependencies
Environment variables
Ports
What to run when the container starts
Purpose: 👉 Build and run the environment where your code/model lives.
“Here is the environment where the model will run.”
🧬 A Modelfile describes how a model (LLM) itself should be built, configured, or fine-tuned.
It typically contains:
Training or quantization instructions
Model hyperparameters (temperature, top_p, top_k)
What tokenizer to use
What parent/base model to load
Weights to import
Metadata about the model
Purpose: 👉 Build, configure, or package the model. Not the environment — the model.
“Here is how the model itself is defined.”
| File | Equivalent To | Purpose |
|---|---|---|
| Dockerfile | Machine setup | Install Linux, Python, deps |
| Modelfile | Model recipe | Load model, set decoding params, training logic |
The parameters like temperature are not environment-related, so they don’t belong in a Dockerfile.