Infrastructure & Compute
Model compression
Techniques that reduce a model's size, cost, or computing requirements.
Example
A smaller representation makes a model cheaper and faster to run.
Why it matters
It makes useful AI capabilities easier to run with limited resources.
You'll hear it
“This version is smaller, but we need to compare its weak spots.”
Can you control it?
Set by the team
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Does compression always mean deleting information?
- Not in the same way. Different methods reduce size or work through different changes.
- Can compression reduce cost without acceptable quality?
- Yes. Savings matter only alongside the ability needed for the task.
- Can a compressed model still need powerful hardware?
- Yes. Smaller does not necessarily mean small enough for every device.