iRender vs Vultr: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for iRender and Vultr. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Attribute

iRender

Vultr

Provider type

Specialist

Founded

2019

2014

Headquarters

Hanoi, Vietnam

Matawan, NJ

Billing model

On-demand (hourly)

Min commitment

None

Support tier

Community → Standard

Basic → 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

Weaknesses

Smaller provider — limited scale vs hyperscalers
Fewer regions than major cloud providers
Less mature ecosystem and fewer integrations

Best For

3D renderingAI trainingAPAC-based teamsCreative workloads

Visit iRender

iRender Rating

No reviews yet — add yours ↗

Vultr

Vultr offers H100, A100, L40S, RTX 6000 Ada, and RTX 4000 Ada GPU instances across 32 global locations with simple hourly billing and no long-term commitment required. A developer-friendly GPU cloud with a clean API, straightforward pricing, and broad geographic coverage for teams needing AI inference or training capacity close to their users. Vultr Cloud GPU instances include dedicated VRAM, NVMe storage, and generous transfer allowances. A solid choice for global deployment of AI workloads without the complexity of hyperscaler pricing models.

Strengths

32 global locations — wide geographic coverage among specialist GPU clouds
Simple hourly billing — no long-term commitment
H100, A100, L40S, RTX 6000/4000 Ada in catalog
Clean API and developer-friendly onboarding
Generous transfer allowances included

Weaknesses

Smaller GPU catalog than specialist AI clouds
Less ML-focused tooling vs CoreWeave or Lambda
Limited spot/preemptible GPU options

Best For

Global deployment of AI workloadsSimple inference and training workloadsDeveloper-friendly teams wanting simple billingTeams needing GPU capacity in emerging regions

Visit Vultr

Affiliate link — we may earn a commission.

Vultr Rating

No reviews yet — add yours ↗