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What are parameters in AI?
Parameters are the many tiny numbers inside an AI model that it adjusts while learning, and they store what it knows.
- Category Models
- Also called model parameters, billion parameters
- Updated 20 Oct 2026
Parameters, explained simply
Picture a huge board of dials. During training, the AI turns the dials a little at a time until its answers improve.
Each dial is a parameter. Bigger models have more of them, often millions or billions.
More parameters can mean more skill, but also more cost and memory. Model names often include the size, like 7B for seven billion.
On ITG Now, our AI models page and free tool guides often mention a model's size in parameters.
Related terms
Model weightsAI modelLLMTrainingNeural networkVRAM
Where you'll see it on ITG Now
- AI newsMicrosoft builds a giant 2.8 trillion parameter AI
- AI newsMicrosoft finishes training its giant MAI-Base-2
- GuideColibri: Run Large AI Models Locally Without a GPU
- AI newsDeepSeek says free model update tops a coding test
- AI newsMeta gives away its big Muse Spark AI for free
- AI newsNew US lab gives away a giant AI free
Questions people ask about Parameters
Are more parameters always better?
Not always. Bigger models often know more, but a well-trained small model can beat a poorly trained big one.
What does 7B mean in a model name?
The B stands for billion. It means the model has about seven billion parameters.