GPU Droplets | DigitalOcean

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Get to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. Scale on demand, spend less on sustained throughput, and deliver actionable insights.
Provision directly from the console or the API.
Connect your GPUs directly to your DigitalOcean Vector Databases, Spaces Object Storage, and Kubernetes clusters—all in one platform.
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Power AI training, inference, and high-performance computing with advanced GPU solutions from AMD and NVIDIA. Contact our sales team to learn more.
Built on the AMD CDNA™ 4 architecture, these GPUs deliver exceptional efficiency and performance for training massive AI models, high-speed inference, and complex HPC workloads including scientific simulations, data processing, and computational modeling.
NVIDIA Blackwell Ultra GPUs deliver significantly expanded AI compute, memory capacity, and networking bandwidth compared to prior-generation Hopper platforms. Combined with DigitalOcean software, NVIDIA B300 delivers higher effective tokens-per-second per dollar, faster model cold-start times, and reliable scaling with improved cost efficiency and predictability. Contact our sales team to learn more.
Use cases: Large model training, fine-tuning, inference, and high-performance computing
Key benefit: Higher memory capacity and improved inference performance compared to MI325X
Use cases: Large model training, fine-tuning, inference, and high-performance computing
Key benefit: High memory capacity to hold models with hundreds of billions of parameters, reducing the need for model splitting across multiple GPUs
Larger memory capacity and higher memory bandwidth vs. MI300X
Use cases: Large model training, fine-tuning, inference, and high-performance computing
Key benefit: High memory bandwidth and capacity to efficiently handle larger models and datasets
Up to 1.3X the performance of AMD MI250X for AI use cases
Use cases: Running large reasoning models and long-context workloads
Key benefit: Reduced model offloading and improved time-to-first-token
Higher sustained throughput under concurrency, more efficient multi-GPU scaling, improved tokens-per-second per dollar
Use cases: Training LLMs, inference, and high-performance computing
Key benefit: Fast inference speeds on LLMs and high memory capacity and bandwidth.
Up to 2x faster inference and improved performance for memory-intensive HPC tasks vs. H100
Use cases: Training LLMs, inference, and high-performance computing
Key benefit: Fast training speed for LLMs
Up to 4X faster training over NVIDIA A100 for GPT-3 (175B) models
Use cases: Inference, graphical processing, rendering, 3D modeling, video, content creation, and media & gaming
Key benefit: Versatile, cost-efficient capabilities for content creation, 3D modeling, rendering, video, and inference workflows
Up to 1.7X higher performance than NVIDIA RTX A4000