Loading Comparison
Fetching pricing data and provider information...
Compare GPU pricing between Spheron and UpCloud. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $0.76/hour between comparable GPUs
| GPU Model ↑ | Spheron Price | UpCloud Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 SXM 80GB VRAM • Spheron | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • SpheronUpCloud | ↑+$0.17(+3.3%) | |||
GH200 96GB VRAM • Spheron | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • SpheronUpCloud | ↑+$0.04(+2.1%) | |||
H200 141GB VRAM • Spheron | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • SpheronUpCloud | ↑+$2.55(+33.2%) | |||
L4 24GB VRAM • UpCloud | Not Available | — | ||
L4 24GB VRAM • | ||||
L40S 48GB VRAM • SpheronUpCloud | ↓$0.32(24.7%) | |||
MI300X 192GB VRAM • Spheron | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 4090 24GB VRAM • Spheron | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Spheron | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • Spheron | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • SpheronUpCloud | ↓$0.73(38.3%) | |||
A100 SXM 80GB VRAM • Spheron | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • SpheronUpCloud | ↑+$0.17(+3.3%) | |||
GH200 96GB VRAM • Spheron | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • SpheronUpCloud | ↑+$0.04(+2.1%) | |||
H200 141GB VRAM • Spheron | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • SpheronUpCloud | ↑+$2.55(+33.2%) | |||
L4 24GB VRAM • UpCloud | Not Available | — | ||
L4 24GB VRAM • | ||||
L40S 48GB VRAM • SpheronUpCloud | ↓$0.32(24.7%) | |||
MI300X 192GB VRAM • Spheron | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 4090 24GB VRAM • Spheron | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Spheron | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • Spheron | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • SpheronUpCloud | ↓$0.73(38.3%) | |||
Explore how these providers compare to other popular GPU cloud services
Compare Spheron with another leading provider
Compare Spheron with another leading provider
Compare Spheron with another leading provider
Compare Spheron with another leading provider
Compare Spheron with another leading provider
Compare Spheron with another leading provider
Access GPU capacity from multiple cloud providers and certified data centers from one account, without separate signups per provider
Instances are billed by the minute rather than rounded up to the hour, past a 20-minute minimum runtime (60 minutes for a 2x AMD MI300X)
NVIDIA instances are typically ready in under two minutes with no approval workflow or provisioning queue
Compute spend across every connected provider is tracked in a single dashboard
Each VM or bare metal instance includes NVMe SSD storage, network bandwidth and full root access, with a dedicated IP on NVIDIA instances
Spheron sources large clusters, specific hardware and InfiniBand configurations from its partner data center network, with a typical quote turnaround of 24-48 hours
No shared hardware — each GPU is always dedicated to a single server with full performance isolation
Helsinki data center powered entirely by renewable energy with up to 90% waste heat recovery for district heating
GDPR-compliant, ISO 27001-certified infrastructure in Finland; UpCloud is also a CISPE member
No egress fees — outbound data transfer is included at no extra cost on all plans, subject to a Fair Transfer Policy
Pay only for active compute time with hourly billing, no rigid contracts or long-term commitments required
Published uptime commitment covering GPU Servers, Premium and Cloud Native servers, and managed databases; entry-level Starter cloud servers carry a 99.99% SLA
On-demand and spot NVIDIA L4, L40S, H100, and B200 GPU instances with dedicated hardware and AMD EPYC processors
Dedicated private cloud infrastructure with NVIDIA L4, L40S, and H200 NVL GPUs
Non-interruptible instances covered by an uptime SLA and billed per minute, with no contract or long-term commitment
Idle capacity on the same hardware at up to 50% off dedicated rates, interruptible when the provider reclaims it
Commit to a duration for locked capacity, volume pricing and dedicated support
Quoted deployments from 8 to 512+ GPUs with specific hardware and InfiniBand configurations sourced from partner data centers
Hourly billing for L4, L40S, H100, and B200 GPU instances with no upfront commitment — pay only for active compute time
Discounted spot pricing for GPU Servers, offering lower hourly rates for interruptible workloads
Fixed monthly pricing for dedicated private cloud GPU infrastructure with L4, L40S, and H200 NVL
Browse available GPU models with live pricing and filter by VRAM, architecture or price
Choose a region, storage and OS image, then deploy; instances are provisioned in around two minutes
SSH in and start working, switch to another GPU model at any time, or spin down to stop per-minute billing
Submit requirements for reserved capacity or custom clusters and Spheron sources, negotiates and sets up the deployment
Sign up at upcloud.com and complete account verification; a 30-day free trial with starting credits is available
Choose from NVIDIA L4, L40S, H100, or B200 GPU configurations with varying vCPU and RAM options
Use pre-configured GPU Ubuntu templates to get started quickly with CUDA and ML frameworks
Add block storage devices (1 GB–4 TB each) from any storage tier for your operating system and data
Capacity sourced from vetted Tier 3/4 partner data centers spanning multiple continents; region is selected at deploy time
Documentation, API reference and changelog at docs.spheron.ai, plus sales contact and call scheduling for reserved capacity and custom cluster quotes
15 data centers across 12 countries spanning Northern Europe, Central Europe, North America, and Asia Pacific; GPU Servers are concentrated in Helsinki, Finland (Telia Helsinki Data Center)
In-house technical support available 24/7 via live chat and email, plus documentation, tutorials, an API reference at developers.upcloud.com, and a public status page