Table of Contents
Quick Answer
- Algorithm: the recipe (e.g., stochastic gradient descent, backpropagation)
- Model: the cake (the trained network with specific weights)
The algorithm is the method; the model is the artifact.
What Do These Terms Mean?
An algorithm is a sequence of steps a computer follows. In ML specifically, it refers to the learning procedure — how weights are updated (Stanford CS229; MIT OpenCourseware).
A model is the resulting function: architecture plus learned parameters. You can run the same algorithm on different data to get different models (Google AI Glossary, 2024).
How Each Works
Algorithm
- Written once in code (e.g., AdamW optimizer)
- Consumes data, produces gradients, updates parameters
- Does not "know" anything specific until trained
Model
- Data structure: architecture (layers) + weights (numbers)
- Runs inference: input -> output
- Serializable (saved to disk as
.safetensors,.ckpt,.bin)
Examples
Algorithms
- Gradient descent
- Backpropagation
- Transformer architecture (also an architecture)
- K-means clustering
- Q-learning
Models
- GPT-4 (weights)
- Llama 3 70B
- Stable Diffusion XL
- BERT-base
- Your fine-tuned support classifier
Algorithm vs Model
| Aspect | Algorithm | Model |
|---|---|---|
| Tangible? | No (pure instructions) | Yes (file on disk) |
| Changes during training | Usually fixed | Yes — weights update |
| Reusable | Across datasets | Specific to one training run |
| Size | A few lines to a few thousand | MB to TB |
| Swapping | Easy | Hard (retrain) |
An architecture like "Transformer" is sometimes called a model family — the combination of architecture + weights is the specific model.
When the Distinction Matters
- Research papers propose new algorithms (attention, Mixture of Experts)
- Products ship specific models (GPT-4o, Claude Sonnet 4.5)
- Licensing: algorithms are rarely licensed; model weights are (Llama 3 license, Mistral license)
- Reproducibility: publishing the algorithm is not enough — sharing weights or training data may be needed
Conclusion
Algorithms are the craft; models are the artifacts. Knowing the difference clarifies licensing, reproducibility, and product discussions. More on Misar Blog.