- Updated: March 3, 2026
- 2 min read
Intel Unveils 288‑Core Xeon “Clearwater Forest” on 18A Process Node – A Game‑Changer for Data Centers
Intel Unveils 288‑Core Xeon “Clearwater Forest” on 18A Process Node – A Game‑Changer for Data Centers
Intel has taken a bold step forward with the debut of its 18‑angstrom (18A) process node, powering the brand‑new 288‑core Xeon 6+ “Clearwater Forest” processors. Designed for hyperscale data‑center workloads, the multi‑chip‑module (MCM) combines six compute dies, each built on the cutting‑edge 18A technology, delivering unprecedented compute density and memory bandwidth.
The new Xeon 6+ family features 12 DDR5‑8000 channels, delivering up to 800 GB/s of memory throughput per socket. With a total of 288 cores, 576 threads, and a massive 3 TB of L3 cache, the chip targets AI inference, high‑performance computing (HPC), and large‑scale cloud services. Intel’s new Foveros 3‑D stacking and Direct 3D Packaging (D3P) technologies enable the tight integration of compute, cache, and I/O, reducing latency and power consumption.
Key highlights include:
- Six 48‑core compute dies (18A) bonded together in a single package.
- 12 DDR5‑8000 memory channels (800 GB/s per socket).
- 3 TB of L3 cache across the MCM.
- Support for PCIe 5.0, CXL 2.0, and AVX‑512 extensions.
- Optimized for AI/ML workloads with dedicated matrix extensions.
Intel positions the Clearwater Forest platform as a direct competitor to AMD’s EPYC 9004 series, promising higher core counts and superior memory bandwidth for the most demanding cloud and AI workloads.
For a deeper dive into the technical specifications, see the original report on Tom’s Hardware.
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Stay tuned for benchmarks and performance analysis as the Clearwater Forest processors become available in the coming months.
Andrii Bidochko
CTO UBOS
Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.