Compute Comparison
vs
All providers →

Runcrate vs GPU.ai: GPU Compute Price Comparison

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

Provider Overview

Provider type
Marketplace
Specialist
Founded
2024
2023
Headquarters
Berlin, Germany
United States
Billing model
On-demand, Spot
On-demand
Min commitment
None
None
Support tier
Community → Standard
Standard
Regions
4 regions
1 regions

Strengths & Best For

Runcrate

Runcrate is a Berlin-based GPU cloud marketplace aggregating bare-metal and VM instances across 21 GPU types and 11 global regions, with some of the lowest starting prices for on-demand GPU rental available anywhere. The marketplace model gives teams access to H100, A100, and a wide range of other GPU SKUs through a single platform, with flexible spot and on-demand billing. A cost-effective option for EU-based teams needing broad GPU variety and multi-region flexibility.

Strengths
  • 21 GPU types
  • 11 global regions
  • Very competitive pricing
  • Bare metal + VM options
Best For
Cost-sensitive teamsMulti-region deploymentsWide GPU variety needs
Visit Runcrate
GPU.ai

GPU.ai provides H100, A100, and L40S cloud GPU instances optimized for AI and ML workloads with a developer-friendly interface and competitive on-demand pricing for training and inference jobs. Straightforward billing and fast provisioning make it accessible for AI developers who want quick access to professional NVIDIA hardware without navigating complex enterprise pricing. A clean, no-frills on-demand GPU cloud for developers building and deploying AI models.

Strengths
  • AI-optimized
  • Developer-friendly
  • Competitive pricing
Best For
AI developersModel trainingInference APIs
Visit GPU.ai

Live GPU Pricing

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

Region Coverage

Popular Comparisons

Runcratemarketplace provider

Runcrate is a Berlin-based GPU cloud marketplace aggregating bare-metal and VM instances across 21 GPU types and 11 global regions, with some of the lowest starting prices for on-demand GPU rental available anywhere. The marketplace model gives teams access to H100, A100, and a wide range of other GPU SKUs through a single platform, with flexible spot and on-demand billing. A cost-effective option for EU-based teams needing broad GPU variety and multi-region flexibility.

GPU.aispecialist provider

GPU.ai provides H100, A100, and L40S cloud GPU instances optimized for AI and ML workloads with a developer-friendly interface and competitive on-demand pricing for training and inference jobs. Straightforward billing and fast provisioning make it accessible for AI developers who want quick access to professional NVIDIA hardware without navigating complex enterprise pricing. A clean, no-frills on-demand GPU cloud for developers building and deploying AI models.

Billing model comparison

Runcrate uses a On-demand, Spot billing model with a minimum commitment of None. GPU.ai uses On-demand 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

Runcrate is best suited for: Cost-sensitive teams, Multi-region deployments, Wide GPU variety needs. Its key strengths are 21 gpu types, 11 global regions, very competitive pricing. GPU.ai is best suited for: AI developers, Model training, Inference APIs. Its key strengths are ai-optimized, developer-friendly, competitive pricing. Marketplace providers aggregate GPU supply from multiple sources, often offering the lowest spot rates but with more variable availability and less predictable performance compared to dedicated providers.

Support tiers and region coverage

Runcrate offers Community → Standard support across 4 regions (EU-Central, US, APAC and 1 more). GPU.ai offers Standard support across 1 region (US). Runcrate's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.

Provider background: Runcrate vs GPU.ai

Runcrate was founded in 2024 and is headquartered in Berlin, Germany. GPU.ai was founded in 2023 and is headquartered in United States. GPU.ai has 1 years more operational history than Runcrate, 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.