AMD Ryzen 8000 Granite Range CPUs will be featuring 170W TDP alongside 16 Zen 5 Cores

AMD is preparing to release its AMD Ryzen 8000 “Granite Ridge” Desktop CPU lineup in 2024, featuring the new Zen 5 core architecture. According to the latest information from Moore’s Law is Dead, AMD’s next-generation desktop CPUs are expected to offer a similar number of cores and TDP. While previous reports covered the Ryzen 8000 APU roadmap, this time the focus is solely on the AMD Ryzen 8000 Desktop CPU lineup.

Based on a server roadmap, the details reveal that the Granite Ridge CPU family mentioned is likely to be part of an embedded lineup rather than the standard desktop parts. Similar to AMD’s Ryzen 5000 Embedded chips, the AMD Ryzen 8000 Embedded CPUs should also support a socketed platform.

However, unlike the embedded lineup, the AMD Ryzen 8000 “Granite Ridge” Desktop CPU family is expected to launch much earlier.

AMD Ryzen 8000
credit: mooreslawisdead

It is anticipated that the chips will be released in the first half of 2024, which seems somewhat optimistic considering the two-year cycle typically followed by AMD between launches. The success of TSMC’s 3nm process node is uncertain, and it remains unknown whether Granite Ridge will use 4nm or opt for 3nm. Recent reports suggest that major tech players may wait until the end of 2024 or even 2025 for 3nm.

The AMD Ryzen 8000 “Granite Ridge” Desktop CPUs will be equipped with Zen 5 cores, codenamed “Nirvana.” These CPUs are expected to feature similar core counts as the current lineup, ranging from 6, 8, 12, and up to 16 cores. The TDPs will also fall within the range of 65-170W, similar to the existing Ryzen 7000 Desktop CPUs. The CPUs are anticipated to incorporate a new and improved cache design.

AMD has confirmed that the new Zen 5 architecture will be launched in 2024. The Zen 5 CPUs will come in three variations (Zen 5 / Zen 5 V-Cache / Zen 5C) and have been designed from scratch, featuring a completely new microarchitecture focused on delivering enhanced performance and efficiency. It includes a re-pipelined front-end, wide issue capabilities, and integrated AI and machine learning optimization.

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