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DataVolt vs Lambda Labs: GPU Compute Price Comparison

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for DataVolt and Lambda Labs. Updated July 2026.

Provider Overview

Provider type
Specialist
Specialist
Founded
2023
2012
Headquarters
Europe
San Francisco, CA
Billing model
On-demand, Spot
On-demand, Reserved (1yr/3yr)
Min commitment
None
None (on-demand)
Support tier
Community → Standard
Community → Enterprise
Regions
1 regions
5 regions

Strengths & Best For

DataVolt

DataVolt is a European GPU cloud offering H100, H200, A100, and L40S instances with competitive on-demand and spot GPU rental pricing, full EU data residency, and straightforward access for AI and ML workloads. Spot availability makes it a cost-effective option for interruptible LLM training and fine-tuning jobs, while on-demand instances suit production inference. A practical European GPU cloud for teams that need GDPR-compliant infrastructure with flexible billing.

Strengths
  • Competitive H100/H200 pricing
  • Spot availability
  • EU data residency
  • Simple pricing
Best For
EU AI teamsCost-sensitive H100 workloadsSpot-tolerant training
Visit DataVolt
Lambda Labs

Lambda Labs offers on-demand and reserved H100, A100, and RTX A6000 GPU instances with simple flat pricing and no egress fees — a refreshing contrast to hyperscaler complexity. Pre-configured PyTorch and TensorFlow environments mean researchers can start LLM training or fine-tuning in minutes without any setup overhead. A go-to on-demand GPU cloud for ML teams that want predictable hourly GPU rental costs without long-term commitments.

Strengths
  • Simple pricing
  • Pre-configured ML stack
  • No egress fees
  • Jupyter notebooks included
Best For
ML researchersDeep learning trainingTeams wanting simplicity
Visit Lambda Labs

Live GPU Pricing

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Region Coverage

Lambda Labs5 regions
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