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Oblivus vs Lambda Labs: GPU Compute Price Comparison

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

Provider Overview

Provider type
Specialist
Specialist
Founded
2022
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
2 regions
5 regions

Strengths & Best For

Oblivus

Oblivus offers H100 and A100 GPU instances on-demand at competitive rates with straightforward pricing and no hidden fees, making it an accessible option for AI training and inference workloads on a budget. Spot GPU rental is also available for further cost savings on interruptible jobs. A no-frills GPU cloud for startups and developers who want simple, transparent pricing without enterprise complexity.

Strengths
  • Low prices
  • Simple pricing
  • No hidden fees
  • H100 availability
Best For
Cost-sensitive trainingBudget AI workloadsStartups
Visit Oblivus
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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