Inference
Inference
The process of running input through a trained model to get a prediction or output.
In depth
The process of running input through a trained model to get a prediction or output. When you send a prompt to an API and get a response, that is inference. Inference cost, speed, and latency are key factors when choosing between AI providers and models.
Example
In practice, developers reach for Inference when they need the capability described above as part of an AI feature or workflow.
Go deeper at Developers Digest
Hands-on guides, comparisons, and tutorials that cover Inference.
FAQ
What is Inference?
The process of running input through a trained model to get a prediction or output.
Why does Inference matter for AI developers?
Inference sits in the Inference part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Inference?
Developers Digest publishes tutorials and videos that cover Inference topics including Inference. Check the blog and YouTube channel for hands-on walkthroughs.
Related terms
Inference
In-Context Learning
The ability of a language model to learn new tasks from examples or instructions provided in the prompt, without any weight updates or training.
Inference
Distillation
A training technique where a smaller "student" model learns to replicate the behavior of a larger "teacher" model.
Inference
Mixture of Experts (MoE)
A model architecture that routes each input to a small subset of specialized sub-networks ("experts") rather than activating the entire model.
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