GPU Compute Pricing

Transparent pricing for A100, H100, and L40S GPUs. Up to 41% cheaper than hyperscalers with enterprise-grade infrastructure.

Save 40-41% on GPU Costs

Train your models for less. A typical 6-month ML project using 8x A100 saves £14,760 compared to AWS.

NVIDIA A100 40GB

FP32: 19.5 TFLOPS | FP16: 312 TFLOPS | Memory: 40 GB HBM2e

Save 41%

Pelagos (Gibraltar)

Hourly:£0.83
Monthly:£600
Annual:£6,600

AWS (Comparison)

Hourly:£1.41
Monthly:£1,020
Annual:£11,220
Ideal Use Cases:
General ML trainingInference at scaleComputer visionNLP models

NVIDIA A100 80GB

FP32: 19.5 TFLOPS | FP16: 312 TFLOPS | Memory: 80 GB HBM2e

Save 41%

Pelagos (Gibraltar)

Hourly:£1.12
Monthly:£810
Annual:£8,910

AWS (Comparison)

Hourly:£1.89
Monthly:£1,370
Annual:£15,070
Ideal Use Cases:
Large language modelsHigh-batch inferenceMulti-modal trainingResearch

NVIDIA H100 80GB

FP32: 51 TFLOPS | FP16: 1,979 TFLOPS | Memory: 80 GB HBM3

Save 41%

Pelagos (Gibraltar)

Hourly:£1.52
Monthly:£1,100
Annual:£12,100

AWS (Comparison)

Hourly:£2.56
Monthly:£1,850
Annual:£20,350
Ideal Use Cases:
GPT-scale LLM trainingUltra-low latency inferenceGenerative AICutting-edge research

NVIDIA L40S

FP32: 91.6 TFLOPS | RT Cores | Memory: 48 GB GDDR6

Save 40%

Pelagos (Gibraltar)

Hourly:£0.97
Monthly:£700
Annual:£7,700

AWS (Comparison)

Hourly:£1.62
Monthly:£1,170
Annual:£12,870
Ideal Use Cases:
Graphics + AI hybridReal-time renderingVideo processingMixed precision

Real-World Cost Examples

WorkloadPelagosAWSYour Savings
Train ResNet-50 (100 epochs)£12.50£21.20£8.70 (41%)
Fine-tune GPT-3 (1B params, 24hrs)£36.50£61.40£24.90 (41%)
Inference: 1M predictions£2.80£4.70£1.90 (40%)
1 year continuous A100 80GB£8,910£15,070£6,160 (41%)

Prices based on A100 80GB usage. AWS prices from EU regions, February 2026.

No Hidden Fees

Simple per-GPU pricing includes storage, network, and support

Flexible Billing

Pay hourly, monthly, or annual with volume discounts available

Instant Scaling

Add or remove GPUs in minutes via API without contract changes

Ready to Save on GPU Costs?

Get £200 in free credits. Deploy your first GPU and see the savings firsthand.

GPU Pricing FAQ

Common questions about GPU compute costs and billing

We offer simple per-GPU pricing with no hidden fees. Prices include compute, memory, storage (up to 1TB NVMe per GPU), network transfer within Gibraltar, and standard support. You're billed hourly with monthly/annual discounts available. Unlike hyperscalers, we don't charge for API calls, data ingress, or inter-GPU communication.
Four factors: (1) Gibraltar's lower operational costs and favorable tax environment, (2) 100% renewable energy reducing power costs by 30%, (3) Efficient liquid cooling enabling higher utilization, (4) Direct-to-customer model without hyperscaler markup. We pass these savings directly to customers while maintaining enterprise-grade infrastructure.
Yes. 1-year commitments receive 10% additional discount, 3-year commitments get 20% off listed prices. For example, a reserved A100 80GB drops to £729/month (1-year) or £648/month (3-year). We also offer flexible reserved capacity—commit to spending level rather than specific GPU count for burstable workloads.
Minimal extras at Pelagos. GPU prices include 1TB NVMe, 20TB monthly egress, and standard support. Additional costs: Extra storage (£0.15/GB/month for NVMe, £0.03/GB/month for object storage), egress over 20TB (£5/TB vs. £75/TB on AWS), and optional premium support (£500-2,000/month depending on tier).
Coming Q3 2026. We're developing a spot market for unused capacity at 50-70% discounts. Unlike hyperscaler spot instances that can terminate anytime, ours guarantee minimum 1-hour runtime with 5-minute termination notice, making them viable for checkpoint-enabled training workloads. Join waitlist for early access.
Multi-GPU within single node: simple multiplication (8x A100 = £4,860/month). Multi-node clusters: add £200/month per node for high-speed interconnect (InfiniBand or RoCE) enabling efficient distributed training. No data transfer costs between nodes. We help optimize topology for your specific framework (PyTorch DDP, DeepSpeed, Megatron).
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