AMD's next-gen Instinct MI400 accelerators will bring separate interposer dies for up to 8 chaplets as spotted in the latest patches.
AMD Instinct MI400 Accelerators Will Utilize the CDNA Next Architecture and Will Have Eight XCDs and Dedicated Multimedia I/O Tiles
It appears that AMD's next-gen Instinct MI400 accelerator will bring significant changes in the design, which reportedly comprise the inclusion of newer tiles. While AMD is still working on the MI350 for release this year, we have started getting information on the Instinct MI400, which is set to launch in 2026.
As per the latest reports, some of the design aspects of the MI400 have been revealed. AMD has yet to provide specs and design information on the MI400 in detail officially, but the latest patches give us a sneak peek into what you should be expecting in the upcoming accelerators.
As spotted by Coelacanth Dream, the new patches available on the Free Desktop show that the MI400 will feature up to Four XCDs (Accelerated Compute Dies), increasing the count from two XCDs per AID on the MI300. That said, there will be two AIDs (Active Interposer Dies) on the MI400 accelerator, and this time, there will be separate Multimedia and I/O dies as well.
For each AID, there will be a dedicated MID tile, and this will offer efficient communication between the compute units and the I/O interfaces compared to what we had in previous generations. Even on the MI350, AMD uses infinity fabric for inter-die communication. So, it's a big change to the MI400 accelerators, which are aimed at large-scale AI training and inference tasks and are going to be based on the CDNA-Next architecture which is probably going to be rebranded to UDNA as part of the red team's unification strategy of the RDNA and CDNA architectures.
Meanwhile, AMD is going to release the MI350 accelerators based on the CDNA 4 architecture this year, which already brings huge improvements over the MI300 and its predecessors. It brings the advanced 3nm process node, higher energy efficiency, and will offer up to a 35-fold increase in AI Inference compared to MI300. The details about the uplifts on MI400 are still unknown, and we await AMD's announcement of its specs and features.
AMD Instinct AI Accelerators:
| Accelerator Name | AMD Instinct MI500 | AMD Instinct MI400 | AMD Instinct MI350X | AMD Instinct MI325X | AMD Instinct MI300X | AMD Instinct MI250X |
|---|---|---|---|---|---|---|
| GPU Architecture | CDNA 6 | CDNA 5 | CDNA 4 | Aqua Vanjaram (CDNA 3) | Aqua Vanjaram (CDNA 3) | Aldebaran (CDNA 2) |
| GPU Process Node | 2nm | 2nm+3nm | 3nm | 5nm+6nm | 5nm+6nm | 6nm |
| XCDs (Chiplets) | TBD | 8 (MCM) | 8 (MCM) | 8 (MCM) | 8 (MCM) | 2 (MCM) 1 (Per Die) |
| GPU Cores | TBD | TBD | 16,384 | 19,456 | 19,456 | 14,080 |
| GPU Clock Speed (Max) | TBD | TBD | 2400 MHz | 2100 MHz | 2100 MHz | 1700 MHz |
| INT8 Compute | TBD | TBD | 5200 TOPS | 2614 TOPS | 2614 TOPS | 383 TOPs |
| FP6/FP4 Matrix | TBD | 40 PFLOPs | 20 PFLOPs | N/A | N/A | N/A |
| FP8 Matrix | TBD | 20 PFLOPs | 5 PFLOPs | 2.6 PFLOPs | 2.6 PFLOPs | N/A |
| FP16 Matrix | TBD | 10 PFLOPs | 2.5 PFLOPs | 1.3 PFLOPs | 1.3 PFLOPs | 383 TFLOPs |
| FP32 Vector | TBD | TBD | 157.3 TFLOPs | 163.4 TFLOPs | 163.4 TFLOPs | 95.7 TFLOPs |
| FP64 Vector | TBD | TBD | 78.6 TFLOPs | 81.7 TFLOPs | 81.7 TFLOPs | 47.9 TFLOPs |
| VRAM | HBM4E | 432 GB HBM4 | 288 GB HBM3e | 256 GB HBM3e | 192 GB HBM3 | 128 GB HBM2e |
| Infinity Cache | TBD | TBD | 256 MB | 256 MB | 256 MB | N/A |
| Memory Clock | TBD | 19.6 TB/s | 8.0 Gbps | 5.9 Gbps | 5.2 Gbps | 3.2 Gbps |
| Memory Bus | TBD | TBD | 8192-bit | 8192-bit | 8192-bit | 8192-bit |
| Memory Bandwidth | TBD | TBD | 8 TB/s | 6.0 TB/s | 5.3 TB/s | 3.2 TB/s |
| Form Factor | TBD | TBD | OAM | OAM | OAM | OAM |
| Cooling | TBD | Passive / Liquid | Passive / Liquid | Passive Cooling | Passive Cooling | Passive Cooling |
| TDP (Max) | TBD | TBD | 1400W (355X) | 1000W | 750W | 560W |
News Source: Videocardz
About the author: Sarfraz Khan is a hardware reporter with a focus on PC components and the builder community. With years of experience writing about PC hardware and laptops, his work has been featured on several reputable technology publications. Sarfraz's hands-on experience is demonstrated through his first-person accounts of using and comparing different hardware configurations, providing practical and relatable insights for everyday users. His technical analysis is respected by peers in the enthusiast community and has been cited by specialized hardware sites such as Germany's Igor's Lab.
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