AMD announces MI350X and MI355X AI GPUs, claims up to 4X generational performance gai

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More power consumption equals lower TCO.
 
  (Image credit: AMD)

AMD unveiled its new MI350X and MI355X GPUs for AI workloads here at its Advancing AI 2025 event in San Jose, California, claiming the new accelerators offer a 3X performance boost over the prior-gen MI300X, positioning the company to improve its competitive footing against its market-leading rival, Nvidia. AMD claims it beats Nvidia in like-for-like inference benchmarks by up to 1.3X and leads by up to 1.13X in select training workloads. 
 
AMD also claims a 4X increase in "AI compute performance" compared to prior-generation AMD MI300X models and a 35X increase in inference performance, largely achieved by transitioning to the CDNA 4 architecture and utilizing a smaller, more advanced process node for the compute chiplets. AMD's production MI350 platforms began shipping last month. 

These two MI300 Series AI GPUs will power AMD rack-level solutions for the remainder of the year and into 2026 as the company builds to its MI400 rollout. 

The MI350X and MI355X share an identical underlying design, featuring up to 288GB of HBM3E memory, up to 8 TB/s of memory bandwidth, and new support for the FP4 and FP6 data types. However, the MI350X is geared for air-cooled solutions with a lower Total Board Power (TBP), while the MI355X pushes power consumption up a notch for liquid-cooled systems geared for the highest performance possible.

AMD MI350X and MI355X specficaitions

AMD will not release an APU version of this chip like it did with last generation's MI300A, which featured both CPU and GPU cores on a single die. In contrast, this generation will have GPU-only designs. 

AMD's MI355X comes with 1.6 times the HBM3E memory capacity of Nvidia's competing GB200 and B200 GPUs, but delivers the same 8TB/s of memory bandwidth. AMD claims a 2X advantage in peak FP64 / FP32 over Nvidia's chips, which isn't surprising given Nvidia's optimization focus on the more AI-friendly lower-precision formats.

Notably, MI350's FP64 matrix performance has been halved compared to MI300X, though vector performance drops by roughly 4% gen-over-gen.

As we move down to lower-precision formats, such as FP16, FP8, and FP4, you can see that AMD generally matches or slightly exceeds the Nvidia comparables. One notable standout is FP6 performance, which runs at FP4 rates, which AMD sees as a differentiating feature. 

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