Inference is the process of running a trained AI model on new input to produce an output. When you ask a language model a question, generate an image from a prompt, or transcribe an audio recording, you are using inference.
Training establishes the model’s learned patterns. Inference uses those patterns to perform a task. In ordinary use, running inference does not retrain the model or permanently teach it from your prompts.
In a local AI studio, inference runs on your own computer rather than a remote service. A model runner or another application loads the model and manages the processing needed to generate a response or result.
Inference speed and memory requirements depend on the model, its precision, the amount of input, and the task. Your GPU, available VRAM, system RAM, and software configuration all influence which workloads your computer can handle comfortably.
