AMD Instinct MI250X

The MI250X uses two CDNA 2 Graphics Compute Dies connected via Infinity Fabric on a single OAM package, effectively acting as a dual-GPU module that software can treat as either two devices or, with careful tuning, closer to a unified one. It was the compute engine behind Oak Ridge National Laboratory's Frontier supercomputer and several other top HPC systems built in 2021-2022.

We'd steer HPC and scientific computing teams toward the MI250X specifically for FP64-heavy simulation codes, climate modeling, computational fluid dynamics, molecular dynamics, where its double-precision throughput still holds up well even against newer AI-focused accelerators that deprioritize FP64. It's a weaker choice for modern LLM training and inference, where the MI300X and MI325X's larger single-package memory pools and AI-tuned FP8/FP16 throughput are a much better fit.

Against the NVIDIA A100 (80GB), the MI250X offers more total memory (128GB vs 80GB) and comparable or better FP64 throughput, which is part of why it won several HPC procurement contracts in its generation. Against AMD's own newer MI300X, the MI250X is meaningfully behind on AI workload throughput and memory bandwidth (3.2 TB/s vs 5.3 TB/s) but can still make sense for existing Frontier-class HPC deployments already built around it. Against the single-die MI210, the MI250X roughly doubles memory, compute units, and power draw, it's the multi-GPU-module big brother in the same CDNA 2 generation. Pricing is enterprise-quote-only; AMD does not publish retail pricing for this class of hardware.