# What is AI Model? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Foundational AI  
> **Canonical Citation:** [https://spidits.com/ai-glossary/models](https://spidits.com/ai-glossary/models)

## Definition
An AI Model is a mathematical algorithm trained on a dataset to perform specific tasks like classification, prediction, or text generation. It represents the saved states of a neural network (the weights and biases) after training, which can be deployed to run inference on new, unseen data.

## Architectural Mechanics & Deep Dive
An AI model is a mathematical algorithm trained on a dataset to perform specific tasks like classification, prediction, or text generation. It represents the saved states of a neural network (the weights and biases) after training, which can be deployed to run inference on new, unseen data.

## Industry Applications & Real-World Use Cases
Model hosting, APIs, and offline model execution

## Frequently Asked Questions

### What is the difference between an algorithm and a model?
An algorithm is the set of rules (like a formula). A model is the specific output generated when an algorithm is trained on actual data.

### How are models deployed?
Models are hosted on servers and accessed via APIs, or run locally on devices using lightweight formats like GGUF or ONNX.

## Related Terminology
- [llm](https://spidits.com/ai-glossary/llm)
- [inference](https://spidits.com/ai-glossary/inference)
- [fine-tuning](https://spidits.com/ai-glossary/fine-tuning)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*