amd

AMD MI250X

CDNA 2–based data center accelerator designed for large-scale AI training and high-performance computing workloads.

Release

2021

GPU Class

Data Center / AI & HPC Accelerator

Architecture

AMD CDNA 2

PRICE SNAPSHOT

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On-premise Module

~$10k–$18k*

Turnkey System

~$120k–$250k†

Cloud Pricing
(per GPU/hr)

~$1.00–$5.00/hr‑

chip identity

AMD MI250X

On-premise Module

MI250X

GPU Class

Data Center / AI & HPC Accelerator

Release

2021

Architecture

AMD CDNA 2

Target Workload

  • Large-scale AI training
  • High-performance computing (HPC) simulations
  • Scientific computing workloads
  • Transformer model training

Distributed machine learning systems

Compatible Platforms

  • AMD Instinct MI250X accelerator modules
  • OEM HPC and AI servers
  • Supercomputing clusters and research computing infrastructure

Interconnect: Infinity Fabric

Software Stack: ROCm, HIP, PyTorch integrations

Ideal Buyer Profile

Organizations that typically deploy MI250X accelerators include:

  • National laboratories and supercomputing centers
  • Academic research institutions
  • AI research teams training large models
  • Enterprises running large-scale simulation workloads

The accelerator is particularly suited for organizations requiring high-performance computing infrastructure that also supports AI training workloads.

Availability Notes

The MI250X is primarily deployed through OEM HPC server platforms and large research computing clusters. Availability is typically focused on enterprise and government computing environments rather than general-purpose cloud infrastructure.

Because of its strong HPC capabilities, the accelerator is commonly integrated into supercomputing systems and specialized research infrastructure.

Recent Developments

  • Deployment in the Frontier supercomputer, one of the world’s fastest HPC systems.
  • Continued adoption of AMD accelerators in scientific computing and research environments.

Development of next-generation AMD Instinct GPUs such as the MI300 series.

overview

The AMD Instinct MI250X is a high-performance accelerator built on AMD’s CDNA 2 architecture, designed to support both artificial intelligence workloads and high-performance computing applications. It represents one of AMD’s flagship accelerators for large-scale compute infrastructure.

The MI250X features a unique dual-die GPU design, integrating two GPU compute dies within a single accelerator package. This architecture significantly increases compute density while enabling high-bandwidth communication between the dies using AMD’s Infinity Fabric interconnect.

With high-bandwidth HBM2e memory and strong double-precision performance, the MI250X is particularly well suited for HPC workloads such as climate modeling, physics simulations, and computational chemistry, while also supporting modern deep learning frameworks for AI training.

Key specifications

MI250X Specifications

MI250X Accelerator Specifications

Specification Value
Architecture AMD CDNA 2
Compute Units 220
Stream Processors ~14,080
Memory 128 GB HBM2e
Memory Bandwidth ~3.2 TB/s
Interconnect Infinity Fabric
Form Factor OAM
Max TDP ~500 W
Precision Support FP64, FP32, FP16, BF16
Typical AI Compute ~383 TFLOPS (FP16)
Process Node TSMC 6 nm
Transistor Count ~58 Billion
Multi-Die Design Dual GPU dies
Multi-GPU Scaling Infinity Fabric links

Performance Summary

  • AI Training: The MI250X delivers strong performance for deep learning training workloads, particularly when deployed in large clusters.
  • HPC Compute: High FP64 throughput makes the accelerator ideal for scientific simulations and research workloads.
  • Memory Capacity: 128 GB of HBM2e memory allows the accelerator to handle large datasets and complex simulation models.
  • Cluster Scaling: Infinity Fabric enables high-bandwidth communication between accelerators in multi-node HPC systems.

The MI250X is widely used in environments where both AI training and scientific computing workloads must be supported by the same infrastructure.

primary use case

  • Large-scale scientific simulations
  • Deep learning training clusters
  • Climate and weather modeling
  • Computational chemistry and physics simulations
  • Academic and research AI workloads

The accelerator is particularly popular in supercomputing environments where AI and HPC workloads overlap.

Alternatives & Upgrade Path

Comparable Accelerators:

  • NVIDIA A100: Widely used GPU for AI training and HPC workloads.
  • NVIDIA H100: Hopper-generation GPU offering higher AI tensor performance.

Upgrade Path:

  • AMD MI300X: Newer CDNA-based accelerator with expanded memory capacity for AI workloads.
  • AMD MI325X: Next-generation variant with increased memory bandwidth.

These accelerators represent AMD’s ongoing development of AI and HPC compute platforms.

Related Chips & Providers

Related AMD Accelerators:

  • MI300X
  • MI325X
  • MI300A

Competing AI Hardware:

  • NVIDIA A100
  • NVIDIA H100
  • Intel Gaudi 3

SUMMARY

The AMD Instinct MI250X is a high-performance accelerator designed for both AI training and high-performance computing workloads. Built on the CDNA 2 architecture, it integrates dual GPU dies, large HBM2e memory capacity, and high-bandwidth Infinity Fabric interconnects to support demanding compute workloads.

Its strong double-precision performance and large memory capacity make the MI250X particularly well suited for scientific simulations, HPC research, and large-scale AI training clusters.

The next chip that should be added is NVIDIA B100.

Why this one next:

  • It’s the primary Blackwell training GPU paired with B200
  • Shows up in many AI cluster announcements
  • Often compared with H100, H200, and B200
  • Important for completing the Blackwell lineup on your site

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