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Jarvis Labs vs iRender: GPU Compute Price Comparison

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

Provider Overview

Provider type
Specialist
Specialist
Founded
2020
2019
Headquarters
San Francisco, CA
Hanoi, Vietnam
Billing model
On-demand (per-second)
On-demand (hourly)
Min commitment
None
None
Support tier
Community → Pro
Community → Standard
Regions
2 regions
3 regions

Strengths & Best For

Jarvis Labs

Jarvis Labs is an ML-focused GPU cloud offering H100, A100, and RTX instances with per-second billing, pre-configured environments for PyTorch, TensorFlow, and other popular frameworks, and a simple interface designed for machine learning engineers. On-demand GPU rental with no minimum commitment makes it easy to spin up and tear down instances for training runs, fine-tuning, and AI inference experiments. A popular choice for ML engineers who want pre-built environments and granular per-second billing.

Strengths
  • Per-second billing
  • Pre-configured ML environments
  • Simple UI
  • Fast provisioning
Best For
ML engineersNotebook-based workflowsTeams wanting pre-built environments
Visit Jarvis Labs
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

Live GPU Pricing

No live pricing data available for these providers right now. View all live GPU prices →

Region Coverage

Popular Comparisons

Jarvis Labsspecialist provider

Jarvis Labs is an ML-focused GPU cloud offering H100, A100, and RTX instances with per-second billing, pre-configured environments for PyTorch, TensorFlow, and other popular frameworks, and a simple interface designed for machine learning engineers. On-demand GPU rental with no minimum commitment makes it easy to spin up and tear down instances for training runs, fine-tuning, and AI inference experiments. A popular choice for ML engineers who want pre-built environments and granular per-second billing.

iRenderspecialist provider

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.

Billing model comparison

Jarvis Labs uses a On-demand (per-second) billing model with a minimum commitment of None. iRender uses On-demand (hourly) billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.

Which workloads each provider suits best

Jarvis Labs is best suited for: ML engineers, Notebook-based workflows, Teams wanting pre-built environments. Its key strengths are per-second billing, pre-configured ml environments, simple ui. iRender is best suited for: 3D rendering, AI training, APAC-based teams, Creative workloads. Its key strengths are competitive apac pricing, rtx 4090 availability, rendering-optimized. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.

Support tiers and region coverage

Jarvis Labs offers Community → Pro support across 2 regions (US, EU). iRender offers Community → Standard support across 3 regions (APAC, US, EU). iRender's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.

Provider background: Jarvis Labs vs iRender

Jarvis Labs was founded in 2020 and is headquartered in San Francisco, CA. iRender was founded in 2019 and is headquartered in Hanoi, Vietnam. iRender has 1 years more operational history than Jarvis Labs, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.