GPU Droplet – NVIDIA RTX 6000 Ada [...], $ 1,130.40/mo. on Linux Cloud
GPU Droplet – NVIDIA RTX 6000 Ada (1x48GB) has been added on Oct 3, 2025, Aggregate Rating (2 out of 10 from 2 reviews)
| 💪 CPU/Cores : | 8 vCPU |
|---|---|
| 🔋 RAM : | 64000 MB |
| 🆓 free domains : | 0 |
| 📌 Dedicated IPs : | 0 |
| 💳 Payment Methods : | Credit / Debit / Prepaid CardsPayPalWire Transfer |
| 🔨 Control Panel : | [In-house] |
| ✍️ Support Options : | Help Desk |
| ⚑ Targeting : | AU FR NL SG US |
| 🚀 Uptime : | 99.99 % |

See also initial GPU Droplet – NVIDIA RTX 6000 Ada (1x48GB) plan location on their website!
*📜 Plan description
Single-GPU AI VM with RTX 6000 Ada: 1 GPU (48 GB VRAM), 8 vCPUs, 64 GB RAM, 500 GB NVMe boot disk, 10,000 GB transfer. On-demand price is $1.57/GPU-hour; monthly converted at 30 days.
All GPU Droplets use simple per-second billing and expose connection, snapshot and resize tooling like standard Droplets. They are designed to run inference, fine-tuning of smaller models and mixed GPU compute with predictable costs. The page also notes accepted payment methods (cards, PayPal; wire via sales), 99.99% uptime SLA for Droplets, and that usage beyond monthly caps is still billed per second. Pricing and specs are subject to change; check the live page during ordering.
All GPU Droplets use simple per-second billing and expose connection, snapshot and resize tooling like standard Droplets. They are designed to run inference, fine-tuning of smaller models and mixed GPU compute with predictable costs. The page also notes accepted payment methods (cards, PayPal; wire via sales), 99.99% uptime SLA for Droplets, and that usage beyond monthly caps is still billed per second. Pricing and specs are subject to change; check the live page during ordering.
📄 Editorial Review
DigitalOcean is a cloud-first provider (founded 2012) that targets developers, startups, and SMBs with simple tooling, predictable pricing, and a broad—but focused—product lineup. Their core compute service, Droplets (Linux VMs on SSD with KVM virtualization), can be deployed in minutes and integrate cleanly with networking, storage, and security features. The platform emphasizes a clean control panel, a mature API/CLI, and rich docs/tutorials so builders can stay productive without hyperscaler complexity.They now span a full IaaS/PaaS mix: Droplets (shared and dedicated CPU families, including Basic/General Purpose/CPU-Optimized/Memory-Optimized/Storage-Optimized), Managed Kubernetes (DOKS) with a free HA control plane and autoscaling, Functions for serverless, and App Platform for fully managed app deployments. Storage options include Spaces (S3-compatible object storage with CDN), Block Storage (Volumes), backups/snapshots, and a Container Registry. Managed data services cover PostgreSQL, MySQL, MongoDB, Valkey, OpenSearch, and Kafka—all designed to offload patching, failover, and routine ops.
DigitalOcean has also moved decisively into AI: Gradient™ AI introduces GPU Droplets and bare-metal GPUs (NVIDIA and AMD), 1-click model deployments, and a managed platform for agentic/LLM workflows. Networking features are practical and developer-friendly: Cloud Firewalls, Load Balancers (with Let’s Encrypt and HTTP/3), VPC and VPC peering, Reserved IPs/BYOIP, IPv6, always-on DDoS protection, and Partner Network Connect for private multi-cloud links.
Timeline
DigitalOcean launched in 2012 (TechStars), quickly expanded infrastructure and community in 2013–2016 with new regions (San Francisco, Frankfurt, Canada, Bangalore) and features like Floating IPs. From 2017–2019, they broadened the platform with research programs (Currents), startup support (Hatch), General Purpose Droplets, and DigitalOcean Kubernetes plus Managed Databases. In 2020 they hosted the Deploy conference and, in 2021, went public while adding serverless capabilities via the Nimbella acquisition. The momentum continued in 2022 with DigitalOcean Functions, DO Impact, Partner Pod, and the acquisition of Cloudways. In 2023, they acquired Paperspace and introduced Gradient™ AI offerings (including Managed Kafka and Premium CPU-Optimized Droplets), signaling a deliberate push into AI/ML alongside their core developer cloud.
Overall, they deliver a balanced combination of simplicity, scale, and price that suits everything from hobby projects to production SaaS.
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