Compute capacity gets the headlines. Power availability is what actually decides who builds, where, and how fast. Power availability and grid capacity now rank as the leading factors in AI infrastructure location decisions. But having power on paper isn't enough. A site needs the capacity to support the workload, a realistic route to getting that power online and the resilience to keep it running. Land without a clear power pathway is an option, not an asset. As @WSP’s Anushka Devaser puts it: “The biggest misunderstanding is assuming securing power is only about price or MW capacity.” AI infrastructure needs more than an available MW figure. It needs firm, resilient power that can support the workload in practice. That’s why land, power and compute need to be considered together. Decisions around one quickly affect what’s possible with the others. Read our Land. Power. Compute. research below.

21.3% → 55.2% MFU. That’s more than a 2× difference in useful work on comparable-era hardware. GPT-3 175B achieved 21.3% MFU. MegaScale reached 55.2%. The difference is not just the GPU. It’s the system around it. DeepSeek-V3 is a useful example. It ran on 2,048 NVIDIA H800 GPUs, hardware built on the same Hopper architecture as the H100 but with NVLink bandwidth reduced from 900 GB/s to 400 GB/s for export compliance. That single difference in interconnect reshaped the entire training strategy. The team avoided tensor parallelism because it was inefficient under the constrained NVLink, built a bidirectional pipeline scheme to overlap computation and communication, and relied on eight 400G InfiniBand NICs per node to compensate for the loss of intra-node bandwidth. The chip was nearly the same. The configuration determined what the cluster could actually do. Even after that hardware-aware co-design, third-party analysis estimates the run landed at around 23% model FLOPs utilization, a figure the DeepSeek team never had to disclose and one that rarely appears in headline infrastructure specifications. GPU model and count only tell part of the story. What matters is how effectively the entire system turns that hardware into useful compute. Read the article below.