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iRender vs Lambda Labs: GPU Compute Price Comparison

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

Provider Overview

Provider type
Specialist
Specialist
Founded
2019
2012
Headquarters
Hanoi, Vietnam
San Francisco, CA
Billing model
On-demand (hourly)
On-demand, Reserved (1yr/3yr)
Min commitment
None
None (on-demand)
Support tier
Community → Standard
Community → Enterprise
Regions
3 regions
5 regions

Strengths & Best For

iRender

iRender is a GPU cloud provider specializing in AI training, 3D rendering, and VFX workloads, offering RTX 4090, A100, and H100 instances with competitive APAC pricing across global nodes. On-demand hourly GPU rental makes it accessible for creative studios and AI teams in Southeast Asia and beyond who need high-performance GPU compute for both rendering pipelines and model training. A strong choice for APAC-based teams that need a single platform for both AI and creative GPU workloads.

Strengths
  • Competitive APAC pricing
  • RTX 4090 availability
  • Rendering-optimized
  • Global nodes
Best For
3D renderingAI trainingAPAC-based teamsCreative workloads
Visit iRender
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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