Top MI300X and MI325X GPU Cloud Providers in 2024

As AI continues to drive the next wave of innovation, the hardware behind these models becomes more critical. AMD’s MI300X and upcoming MI325X accelerators are rising as key players in the AI infrastructure space. With a focus on performance, scalability, and energy efficiency, these accelerators have become central to cloud providers offering next-generation AI compute solutions. Below, we explore some of the top cloud platforms adopting AMD’s Instinct MI300X and MI325X GPUs in 2024.

Top MI300X and MI325X GPU Cloud Providers

1. Vultr (vultr.com)

Vultr, a leading privately held cloud computing provider, is making waves by integrating AMD Instinct MI300X accelerators into its scalable cloud infrastructure. The goal? To manage GPU-accelerated workloads with unparalleled efficiency, whether it’s across data centers or edge computing environments.

With the MI300X’s ability to handle high-performance tasks, Vultr can deliver seamless, scalable performance for its customers, positioning itself as a strong alternative to larger cloud platforms. As AI workloads continue to grow in complexity, Vultr’s adoption of AMD’s cutting-edge hardware signals its commitment to delivering premium compute power at scale.

2. Microsoft Azure (azure.microsoft.com)

Azure, one of the world’s most well-known cloud platforms, has also turned to AMD’s MI300X accelerators. Through its ND MI300X virtual machines (VMs), Azure provides high-performance AI compute power for workloads ranging from large language model (LLM) inference to complex AI training tasks.

These MI300X-powered VMs are designed for customers needing extreme performance and reliability. For instance, Azure’s AI Production workloads, including its Azure OpenAI Service, benefit from the immense power of these accelerators. By enabling access to GPT-3.5 and GPT-4 models, Azure ensures that enterprises can deploy AI applications at scale with unparalleled speed and efficiency.

3. Oracle Cloud Infrastructure (OCI) (oracle.com/cloud)

Oracle Cloud Infrastructure (OCI) has stepped up its game by integrating AMD Instinct MI300X accelerators into its newest Compute Supercluster instance. This high-performance cloud solution is optimized for running demanding AI workloads, including LLM inference and training.

Oracle’s adoption of AMD’s ROCm open software, alongside the MI300X, provides a flexible and high-performance solution that supports vast GPU clusters—up to 16,384 GPUs interconnected within an ultrafast network fabric. Companies like Fireworks AI have already adopted this cutting-edge infrastructure to fuel their AI-powered services.

4. TensorWave (tensorwave.com)

Las Vegas-based startup TensorWave is positioning itself as a powerful player in the AI infrastructure space, with plans to deploy thousands of MI300X accelerators. Armed with recent funding, TensorWave is preparing to launch an inference service leveraging the MI300X in the fourth quarter of 2024.

TensorWave’s focus on using the MI300X’s high memory capacity and bandwidth is particularly geared toward retrieval-augmented generation (RAG) use cases, a key component in advanced AI systems. By utilizing the MI300X, TensorWave is setting itself up to offer efficient, high-performance AI services that are ready to compete with the giants in the industry.

The AMD MI300X & MI325X Advantage

The AMD MI300X, with its high memory capacity and bandwidth, is an attractive option for companies looking to handle massive AI workloads with speed and precision. Its upcoming successor, the MI325X, is expected to build on this performance with even greater efficiency and power.

Cloud providers integrating these GPUs into their infrastructure are giving enterprises a competitive alternative to Nvidia’s widely used accelerators. As AI continues to expand into new applications, having the right hardware in place is crucial, and AMD’s accelerators are proving to be a compelling choice.