What is latency?

Latency is the delay between the moment an AI system receives an input and the moment it delivers an output. It reflects how quickly a model can process information and respond.

How does latency work?

Latency measures the full chain of events involved in producing a prediction or response. That chain typically includes:

• Preparing or formatting the input data.
• Running computations inside the model.
• Moving data between CPUs, GPUs, or other accelerators.
• Generating and formatting the final output.

Larger and more complex models usually have higher latency because they require more computation. Other factors, such as inefficient data transfer or unoptimized code, also increase response time.

Lowering latency often involves simplifying model architecture, optimizing inference routines, compressing or quantizing models, and running workloads on faster hardware. Improvements like specialized accelerators and greater memory bandwidth further reduce delays.

Latency directly affects how responsive an AI system feels. A slow model produces noticeable lag, while a low-latency model supports smooth, real-time interactions. The acceptable amount of delay depends on the use case. For instance, conversational systems require very quick turnarounds to feel natural.

Why is low latency important?

Low latency matters because it determines whether an AI system is usable and enjoyable. Quick responses support natural interactions and prevent the friction caused by long delays. Many real-time applications — such as voice assistants, autonomous systems, or interactive analytics — simply cannot function with high latency.

Reducing delay also makes it possible to deploy more complex models in time-sensitive settings. When outputs arrive quickly, new classes of products and experiences become feasible. Low latency ultimately broadens what AI can do while improving overall user satisfaction.

Why does low latency matter for companies?

For companies, low latency unlocks real-time AI capabilities across customer experience, operations, and decision-making. Chatbots, voice agents, recommendation engines, fraud-detection systems, and supply-chain tools all depend on rapid responses to be effective.

Faster AI systems improve customer interactions, increase employee efficiency, and support quick reactions to emerging issues. They also open the door to new features and competitive advantages that sluggish systems cannot deliver. Organizations that invest in reducing latency gain smoother workflows, better insights, and more engaging AI-powered experiences.