MI250 GPU
The AMD Instinct MI250 is a data center GPU accelerator with 128GB HBM2e memory for AI and HPC workloads.

Cloud Pricing
Prices updated daily. Last check: 4/8/2026
Performance
Strengths & Limitations
- 128 GB HBM2e memory capacity enables training of large models without memory constraints
- 3.2 TB/s memory bandwidth supports memory-intensive computational workloads
- 362.1 TFLOPs FP16 performance delivers high throughput for AI training tasks
- 45.3 TFLOPs FP64 performance per GPU die supports scientific computing applications
- 8 Infinity Fabric Links with 100 GB/s bandwidth enable efficient multi-GPU scaling
- AMD ROCm ecosystem provides open-source software stack without vendor lock-in
- TSMC 6nm FinFET manufacturing process offers improved power efficiency over older nodes
- 500W TDP requires substantial cooling infrastructure and power delivery
- AMD ROCm ecosystem has smaller software library compared to CUDA
- Released in 2021, now superseded by newer GPU generations from both AMD and NVIDIA
- OAM form factor limits deployment flexibility compared to PCIe add-in cards
- May be overkill for inference workloads that don't require 128 GB memory capacity
Key Features
About MI250
Common Use Cases
The MI250 is designed for large-scale AI training and high-performance computing workloads that require substantial memory capacity and computational throughput. Its 128 GB memory makes it suitable for training large language models, computer vision models with high-resolution datasets, and scientific simulations that process large amounts of data. The high FP64 performance makes it particularly valuable for scientific computing applications in computational fluid dynamics, molecular dynamics, and weather modeling. Organizations using AMD's ROCm ecosystem or seeking alternatives to NVIDIA's platform will find the MI250 effective for distributed training across multiple nodes.
Full Specifications
Hardware
- Manufacturer
- AMD
- Architecture
- CDNA 2
- TDP
- 500W
Memory & Performance
- VRAM
- 128GB
- Memory Bandwidth
- 3276 GB/s
- FP16
- 362 TFLOPS
- FP64
- 45.26 TFLOPS
- Release
- 2021
Frequently Asked Questions
How much does a MI250 cost per hour in the cloud?
MI250 pricing varies by provider, region, and commitment level. Check the pricing table above for current rates across all providers.
What is the MI250 best used for?
The MI250 is best suited for large-scale AI training, scientific computing, and HPC workloads that require substantial memory capacity. Its 128 GB HBM2e memory and high FP64 performance make it particularly effective for training large language models and running scientific simulations.
How does the MI250 compare to NVIDIA's H100 for AI training?
The MI250 offers 128 GB of memory compared to the H100's 80 GB, providing advantages for memory-intensive workloads. However, the H100's Transformer Engine and newer Hopper architecture generally deliver better performance per watt for modern AI training. The choice often depends on memory requirements and software ecosystem preferences between ROCm and CUDA.