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AMD launched its Instinct MI300 Series on December 6, 2023, with two different data-center products: MI300X, a GPU accelerator for AI workloads, and MI300A, an APU that combines CPU and GPU compute for high-performance computing (HPC) and AI. Microsoft, Dell and HPE announced distinct cloud and system plans involving the chips; their support was not one joint endorsement or a single shared deployment. AMD’s claim that MI300X can outperform Nvidia H100 on a particular AI inference test is a company-run benchmark, not an independent verdict on the broader Nvidia challenge.
What AMD launched: MI300X and MI300A
AMD announced the MI300 Series on December 6, 2023. Both products use AMD’s CDNA 3 GPU architecture, but they are designed for different system roles. AMD said MI300X accelerators were available at launch; it introduced MI300A as a data-center APU for HPC and AI. The specifications below are AMD’s manufacturer figures from the launch announcement.
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AMD Radeon Instinct MI210 64GB HBM2 300W PCIe Dual Slot Full Height Graphics Accelerator | $5,249.99 | Buy on Amazon |
| Chip | Design and intended workloads | Memory |
|---|---|---|
| MI300X | GPU accelerator aimed at large language model (LLM) training and inference | 192 GB HBM3 per accelerator; AMD lists peak memory bandwidth of 5.3 TB/s per accelerator |
| MI300A | APU combining Zen 4 x86 CPU cores and CDNA 3 GPU cores for HPC and AI | 128 GB HBM3; AMD describes the CPU and GPU as sharing unified memory and cache resources |
In practical terms, MI300X is the GPU-focused choice for systems built around accelerators. MI300A integrates CPU and GPU compute in one package, a design intended for workloads that benefit from bringing those resources and their memory together.
How the MI300X platform differs from one accelerator
AMD’s MI300X product page describes an eight-accelerator Universal Baseboard 2.0 platform. It lists 1.5 TB of aggregate memory for the platform and 5.3 TB/s of memory bandwidth per OAM accelerator. Those numbers describe different levels: 192 GB is the capacity of one MI300X accelerator, while 1.5 TB is the aggregate capacity AMD lists for the eight-accelerator platform. [AMD Instinct MI300X product specifications]
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This is data-center infrastructure, not a consumer graphics card. The announced platform uses eight OAM accelerators; the launch evidence does not establish an ordinary retail graphics-card version.
What Microsoft, Dell and HPE announced
“Backing” refers to separate cloud and hardware announcements. The examples differ in which MI300 product they use and how customers would access it.
| Partner | Announced MI300 connection | What it means |
|---|---|---|
| Microsoft | Azure ND MI300X v5 virtual machine series, optimized for AI and powered by MI300X | A cloud route to MI300X capacity rather than an announcement of a Microsoft-branded chip |
| Dell | PowerEdge XE9680 server configuration featuring eight MI300 Series accelerators, plus a Dell Validated Design for Generative AI using ROCm-powered frameworks | An OEM server and validated software-design route for organizations deploying accelerator systems |
| HPE | Cray Supercomputing EX255a accelerator blade powered by MI300A, with broader planned MI300 offerings across enterprise and HPC products | An HPC-oriented system using MI300A; it is not the same MI300X cloud example announced by Microsoft |
AMD’s June 2, 2024 release also named Microsoft Azure, Meta, Dell Technologies, HPE and Lenovo among MI300X customers and partners. That is later adoption information reported by AMD, not a current inventory statement or confirmation of availability in every region. [AMD’s June 2, 2024 data-center AI portfolio announcement]
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How strong is the Nvidia challenge?
AMD said its Instinct platform could deliver up to 1.6 times the inference throughput of Nvidia H100 HGX when running BLOOM 176B. That figure comes from AMD Performance Labs testing dated November 17, 2023: an eight-MI300X system with a pre-release ROCm 6.0 configuration was compared with eight Nvidia H100 GPUs in an Nvidia DGX H100. The systems used different software configurations. AMD also cautioned that server configurations, drivers and optimizations can affect performance. [AMD’s MI300 launch announcement and benchmark notes]
So the 1.6x result is evidence of AMD’s performance claim under one specified test, not proof that MI300X is faster for every model, software stack or production workload. The reviewed sources establish no independent comparative benchmark or market-share statistic. A fair purchasing comparison would need the same workload, software versions and system configurations, as well as power, availability and total cost—not just a peak memory figure or one vendor’s test.
What the launch does and does not establish
The launch established two substantial data-center products and named pathways to cloud and OEM systems. AMD positioned MI300X for LLM training and inference and MI300A for CPU-GPU HPC and AI workloads. The partner announcements show interest in offering or integrating the hardware, but they do not by themselves establish comparative performance across workloads, current system inventory, geographic availability or pricing.
For teams considering MI300, the relevant question is which system and software configuration fits their workload: cloud access through a supported VM, an OEM server such as Dell’s PowerEdge XE9680, or an HPC system such as HPE’s Cray EX255a. These are enterprise infrastructure decisions, not consumer GPU shopping.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
