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Compare GPU and LLM inference API pricing between DigitalOcean and Packet AI. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $1.03/hour between comparable GPUs
| GPU Model ↑ | DigitalOcean Price | Packet AI Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 SXM 80GB VRAM • Packet AI | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Packet AI | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 SXM 80GB VRAM • DigitalOcean | 8x GPU | Not Available | — | |
H100 SXM 80GB VRAM • $2.99/hour 8x GPU configuration Updated: 7/16/2026 ★Best Price Not Available | ||||
H200 141GB VRAM • DigitalOcean | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • DigitalOceanPacket AI | ↑+$1.03(+190.7%) | |||
L40S 48GB VRAM • $1.57/hour Updated: 7/16/2026 $0.54/hour Updated: 7/3/2026 ★Best Price Price Difference:↑+$1.03(+190.7%) | ||||
MI300X 192GB VRAM • DigitalOcean | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • DigitalOcean | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • DigitalOcean | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX 6000 Pro 96GB VRAM • Packet AI | Not Available | — | ||
RTX 6000 Pro 96GB VRAM • | ||||
A100 SXM 80GB VRAM • Packet AI | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Packet AI | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 SXM 80GB VRAM • DigitalOcean | 8x GPU | Not Available | — | |
H100 SXM 80GB VRAM • $2.99/hour 8x GPU configuration Updated: 7/16/2026 ★Best Price Not Available | ||||
H200 141GB VRAM • DigitalOcean | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • DigitalOceanPacket AI | ↑+$1.03(+190.7%) | |||
L40S 48GB VRAM • $1.57/hour Updated: 7/16/2026 $0.54/hour Updated: 7/3/2026 ★Best Price Price Difference:↑+$1.03(+190.7%) | ||||
MI300X 192GB VRAM • DigitalOcean | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • DigitalOcean | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • DigitalOcean | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX 6000 Pro 96GB VRAM • Packet AI | Not Available | — | ||
RTX 6000 Pro 96GB VRAM • | ||||
Explore how these providers compare to other popular GPU cloud services
Compare DigitalOcean with another leading provider
Compare DigitalOcean with another leading provider
Compare DigitalOcean with another leading provider
Compare DigitalOcean with another leading provider
Compare DigitalOcean with another leading provider
Compare DigitalOcean with another leading provider
On-demand NVIDIA and AMD GPU instances with per-hour billing and no long-term contracts.
Pre-configured images with PyTorch, TensorFlow, and CUDA for immediate productivity.
GPU Droplets work seamlessly with DigitalOcean's networking, storage, and managed databases.
Transparent per-hour pricing with no hidden fees or complex instance families.
Direct SSH access to GPU instances with full root control and native performance
VS Code and Jupyter environments accessible directly in the browser
Drop-in replacement for OpenAI APIs with automatic model discovery and streaming support
Deploy GPU instances in under 5 minutes without procurement cycles or contracts
Advanced scheduling technology that optimizes GPU utilization and reduces costs
Pay per second with no long-term commitments or minimum usage requirements
Advanced resource optimization that reduces costs by eliminating idle GPU time
Sign up at digitalocean.com and verify your account.
Select GPU Droplets from the Create menu, choose your GPU type and configuration.
Select a pre-configured AI/ML image or a base OS image.
Launch your GPU Droplet and connect via SSH to start working.
Quick account creation with no credit card required to start
Choose from available NVIDIA GPUs including RTX Pro 6000, H200s, and B200s
Instance ready in under 5 minutes with SSH access or web dashboard
GPU Droplets are available in select US data centers with expansion planned.
24/7 support via ticket system, extensive documentation, and active community forums.