DigitalOcean Launches AMD MI350X GPU Droplets to Boost AI Inference Performance

DigitalOcean has introduced new high-performance GPU Droplets powered by Advanced Micro Devices’ AMD Instinct MI350X GPUs, further strengthening its Agentic Inference Cloud for production-scale AI. With this move, the company aims to deliver greater performance, improved efficiency, and cost predictability for AI-native businesses scaling inference-heavy workloads.

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By integrating AMD Instinct MI350X GPUs into its infrastructure, DigitalOcean enables customers to optimize production inference with lower latency and higher throughput. These GPUs, built on AMD’s CDNA 4 architectures, are engineered for generative AI and high-performance computing (HPC). As a result, organizations can train massive AI models, process large datasets, and run complex scientific simulations with enhanced efficiency.

Moreover, the MI350X GPUs allow DigitalOcean to optimize compute-bound prefill phases while supporting larger models and expanded context windows. Consequently, developers can handle higher inference request density per GPU, improve token generation throughput, and maintain consistent low-latency performance. When paired with DigitalOcean’s inference-optimized platform, these enhancements translate into measurable operational gains.

“These results demonstrate that the DigitalOcean Agentic Inference Cloud isn’t just about providing raw compute, but about delivering the operational efficiency, inference optimizations, and scale required for demanding AI builders,” said Vinay Kumar, Chief Product and Technology Officer at DigitalOcean. “The availability of the AMD Instinct MI350X GPUs, combined with DigitalOcean’s inference optimized platform offers our customers a boost in performance and the massive memory capacity needed to run the world’s most complex AI workloads while delivering compelling unit economics.”

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Earlier this year, DigitalOcean revealed that optimizing AMD Instinct GPUs helped deliver 2X production request throughput and a 50% reduction in inference costs for Character.AI. Building on that momentum, companies like ACE Studio are now leveraging MI350X GPUs to power advanced inference workloads while keeping operational costs in check.

“At ACE Studio, our mission is to build an AI-driven music workstation for the future of music creation,” said Sean Zhao, Co-Founder & CTO. “As we expand our footprint on DigitalOcean, the next-generation AMD Instinct MI350X architecture, supported by close collaboration on inference optimization with AMD and DigitalOcean, provides us a strong foundation to push performance and cost efficiency even further for our customers.”

Furthermore, AMD emphasized the strategic importance of this partnership. “Our collaboration with DigitalOcean is rooted in a shared commitment to pairing leadership AI infrastructure with a platform designed to make large-scale AI applications more accessible to the world’s most ambitious developers and enterprises,” said Negin Oliver, Corporate Vice President of Business Development, Data Center GPU Business at AMD. “By bringing the AMD Instinct MI350 Series GPUs to DigitalOcean’s Agentic Inference Cloud, we are empowering startups and enterprises alike to deploy and scale next-generation AI workloads with confidence.”

Notably, this launch builds on previous joint initiatives, including the rollout of the AMD Developer Cloud and earlier availability of MI300X and MI325X GPUs on DigitalOcean.

In addition to performance improvements, DigitalOcean continues to prioritize simplicity and cost transparency. The company offers usage-based pricing with no hidden fees, streamlined GPU Droplet setup, enterprise-grade SLAs, observability features, and compliance standards such as HIPAA eligibility and SOC 2 certification.

Currently, DigitalOcean provides the new AMD Instinct MI350X-powered GPU Droplets in its Atlanta region data center, with plans to deploy AMD Instinct MI355X GPUs next quarter. This upcoming expansion will introduce liquid-cooled racks and further enhance support for larger AI models and datasets solidifying DigitalOcean’s position as a scalable, cost-efficient AI infrastructure partner.

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