Kilobyte per second to Tebibyte per second

A typical 4 MB MP3 file at 7 kB/s took about 9–10 minutes to download. Napster users in 1999 would queue up songs before bed and hope the phone line stayed connected overnight. A single disconnection meant starting over from scratch.

Lowercase "k" with uppercase "B" (kB/s) means 1,000 bytes per second (SI decimal). Uppercase "K" with uppercase "B" (KB/s) traditionally meant 1,024 bytes per second (binary). In practice, most software uses them interchangeably, and the difference is only 2.4%.

Apps display kB/s when transfer speeds are genuinely that slow — downloading over congested mobile networks, tethering in rural areas, or transferring tiny files where the connection never ramps up. It is also common in SSH/SCP transfers that display instantaneous speed during small file copies.

The first consumer ADSL plans offered 256 kbps downstream, delivering about 32 kB/s — roughly 4.5× faster than a 56k modem. A 512 kbps plan gave 64 kB/s. That first jump from 7 to 32 kB/s felt revolutionary, cutting a 10-minute download to about 2 minutes.

An SMS is limited to 140 bytes (160 characters in GSM-7 encoding), and the signalling channel transmits it almost instantly. But if you think of SMS throughput over a sustained period, the practical rate is about 0.1–0.5 kB/s because of the overhead between messages.

AMD's MI300X stacks 8 HBM3 memory modules and multiple compute chiplets on a single package using advanced 2.5D packaging with silicon interposers. The short physical distance between compute and memory dies — millimeters instead of centimeters — dramatically reduces signal latency and power per bit. This allows a 5.3 TB/s aggregate bandwidth that would be physically impossible with traditional socketed memory. The trend toward chiplet packaging is how the industry keeps scaling bandwidth despite hitting limits in single-die manufacturing.

Significantly. When provisioning an AI training cluster with hundreds of GPUs, a 10% bandwidth miscalculation cascades through the entire system design — buffer sizes, interconnect capacity, cooling, and power. Getting the units wrong could mean the difference between a training run finishing in 30 days vs 33 days.

Training large language models (100B+ parameters), molecular dynamics simulations, weather modeling, and fluid dynamics at scale. These workloads move enormous matrices through memory billions of times. The TiB/s memory bandwidth of modern GPUs is what makes training models like GPT-4 possible in months rather than decades.

Memory bandwidth dwarfs network bandwidth. Each H100 GPU has 3.35 TiB/s of internal memory bandwidth but connects to the network at only 0.05 TiB/s (400 Gbps InfiniBand). This 60:1 ratio is why AI chip designers obsess over keeping computations local to each GPU and minimising network communication.

Not in the same way. Quantum computers process information through qubits that exist in superposition, so they do not shuttle classical data around at TiB/s. However, the classical control systems that manage quantum processors and process measurement results do need high bandwidth — current quantum-classical interfaces operate at modest Gbps rates.