Picture the planning meeting for a small inference team.
The model works, the queue is growing, and the only thing standing between the team and paying customers is a rack that can hold the hardware.
For years the answer was more power.
Flagship inference accelerators now run in liquid-cooled racks measured in kilowatts.
Intel canceled two data center GPU attempts on that road, Rialto Bridge in 2023 and Falcon Shores in 2025.
At this week's Open Compute Project Global Summit, Intel named the counter-move instead.
Crescent Island arrives as the GPU D-Series, headlined by the D270.
It serves a theoretical 1.3 PFLOPS of FP8 with up to 480GB of LPDDR5X at 1.5 TB/s, in a 350 watt air-cooled PCIe Gen5 card.
Intel's own positioning is unusual for this market: not on the same performance level as the flagships, and a lot smaller and cheaper as a result.
It is the first commercial AI data center GPU from Intel since Ponte Vecchio in 2021.
That is the part worth sitting with if you are the team waiting for capacity.
The bottleneck on shipping an inference product has been the building around the chip: power budget, cooling, allocation queues.
BHK Cloud rents RTX 3090 capacity at $0.15/hr and cloud storage at $2.49/TB per month, with Buy Now Pay Later.
Zero upfront, payment after one month.
Capacity comes online without a rack build or a cooling loop.
If you could start serving a model this week, what would you put in front of real users first?
https://ai.bhkcloud.com/?utm_source=linkedin&utm_medium=social&utm_campaign=bhk_social_2026w42&utm_content=morning
Originally posted on linkedin_personal