Network throughput (or just throughput, when in context) refers to the rate of message delivery over a communication channel in a communication network, such as Ethernet or packet radio. The data that these messages contain may be delivered over physical or logical links, or through network nodes. Throughput is usually measured in bits per second (bit/s, sometimes abbreviated bps), and sometimes in packets per second (p/s or pps) or data packets per time slot.

The aggregate throughput is the sum of the data rates that are delivered over all channels in a network. Throughput represents digital bandwidth consumption.

The throughput of a communication system may be affected by various factors, including the limitations of the underlying physical medium, available processing power of the system components, end-user behavior, etc. When taking various protocol overheads into account, the useful rate of the data transfer can be significantly lower than the maximum achievable throughput; the useful part is usually referred to as goodput.

Users of telecommunications devices, systems designers, and researchers into communication theory are often interested in knowing the expected performance of a system. From a user perspective, this is often phrased as either "which device will get my data there most effectively for my needs?", or "which device will deliver the most data per unit cost?". Systems designers often select the most effective architecture or design constraints for a system, which drive its final performance.

In most cases, the benchmark of what a system is capable of, or its maximum performance is what the user or designer is interested in. The term maximum throughput is frequently used when discussing end-user maximum throughput tests. Maximum throughput is essentially synonymous with digital bandwidth capacity.

Four different values are relevant in the context of maximum throughput are used in comparing the upper limit conceptual performance of multiple systems. They are maximum theoretical throughput, maximum achievable throughput, peak measured throughput, and maximum sustained throughput. These values represent different qualities, and care must be taken that the same definitions are used when comparing different maximum throughput values.

Each bit must carry the same amount of information if throughput values are to be compared. Data compression can significantly alter throughput calculations, including generating values exceeding 100% in some cases.

Maximum theoretical throughput is closely related to the channel capacity of the system, and is the maximum possible quantity of data that can be transmitted under ideal circumstances. In some cases, this number is reported as equal to the channel capacity, though this can be deceptive, as only non-packetized systems technologies can achieve this. Maximum theoretical throughput is more accurately reported taking into account format and specification overhead with best-case assumptions.

The asymptotic throughput (less formal asymptotic bandwidth) for a packet-mode communication network is the value of the maximum throughput function, when the incoming network load approaches infinity, either due to a message size, or the number of data sources. As with other bit rates and data bandwidths, the asymptotic throughput is measured in bits per second (bit/s) or (rarely) bytes per second (B/s), where 1 B/s is 8 bit/s. Decimal prefixes are used, meaning that 1 Mbit/s is 1000000 bit/s.

Asymptotic throughput is usually estimated by sending or simulating a very large message (sequence of data packets) through the network, using a greedy source and no flow control mechanism (i.e., UDP rather than TCP), and measuring the volume of data received at the destination node. Traffic load between other sources may reduce this maximum network path throughput. Alternatively, a large number of sources and sinks may be modeled, with or without flow control, and the aggregate maximum network throughput measured (the sum of traffic reaching its destinations).

In a network simulation model with infinitely large packet queues, the asymptotic throughput occurs when the network latency (due to packet queuing time) goes to infinity, while if the packet queues are limited, or the network is a multi-drop network with many sources, and collisions may occur, the packet-dropping rate approaches 100%.

As well as its use in general network modeling, asymptotic throughput is used in modeling performance on massively parallel computer systems, where system operation is highly dependent on communication overhead, as well as processor performance. In these applications, asymptotic throughput is used modeling which includes the number of processors, so that both the latency and the asymptotic throughput are functions of the number of processors.

Where asymptotic throughput is a theoretical or calculated capacity, peak measured throughput is throughput measured on a real implemented system, or on a simulated system. The value is the throughput measured over a short period of time; mathematically, this is the limit taken with respect to throughput as time approaches zero. This term is synonymous with instantaneous throughput. This number is useful for systems that rely on burst data transmission; however, for systems with a high duty cycle, this is less likely to be a useful measure of system performance.