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GPUhub vs Lambda Labs: GPU Compute Price Comparison

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

Provider Overview

Provider type
Specialist
Specialist
Founded
2021
2012
Headquarters
Ho Chi Minh City, Vietnam
San Francisco, CA
Billing model
On-demand
On-demand, Reserved (1yr/3yr)
Min commitment
None
None (on-demand)
Support tier
Standard
Community → Enterprise
Regions
2 regions
5 regions

Strengths & Best For

GPUhub

GPUhub is a Southeast Asian GPU cloud based in Vietnam, offering H100, A100, and RTX instances at affordable APAC pricing for AI and ML workloads across the region. On-demand billing and local support make it one of the most accessible GPU cloud options for Vietnamese and Southeast Asian teams running LLM training, fine-tuning, and inference workloads. A strong regional option for APAC-based developers who want low-latency GPU access at competitive local prices.

Strengths
  • APAC presence
  • Affordable pricing
  • Local support
Best For
Southeast Asian teamsCost-sensitive AI workloadsAPAC inference
Visit GPUhub
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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