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TensorDock vs Runcrate: GPU Compute Price Comparison

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

Provider Overview

Provider type
Specialist
Marketplace
Founded
2020
2024
Headquarters
Boston, MA
Berlin, Germany
Billing model
On-demand, Spot
On-demand, Spot
Min commitment
None
None
Support tier
Community → Pro
Community → Standard
Regions
4 regions
4 regions

Strengths & Best For

TensorDock

TensorDock offers H100, A100, RTX 4090, and RTX 3090 GPU instances across a distributed network of data centers at some of the most competitive on-demand and spot GPU rental prices available. Both on-demand and spot options are available, making it a popular budget AI training platform for cost-sensitive teams and researchers. A practical choice for LLM fine-tuning and batch inference workloads where price-per-GPU-hour is the primary concern.

Strengths
  • Very low prices
  • Wide GPU variety
  • Spot instances
  • Global locations
Best For
Budget ML trainingBatch inferenceCost-sensitive teams
Visit TensorDock
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

Live GPU Pricing

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

Region Coverage

Runcrate4 regions
EU-CentralUSAPACVarious

Popular Comparisons

TensorDockspecialist provider

TensorDock offers H100, A100, RTX 4090, and RTX 3090 GPU instances across a distributed network of data centers at some of the most competitive on-demand and spot GPU rental prices available. Both on-demand and spot options are available, making it a popular budget AI training platform for cost-sensitive teams and researchers. A practical choice for LLM fine-tuning and batch inference workloads where price-per-GPU-hour is the primary concern.

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.

Billing model comparison

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

TensorDock is best suited for: Budget ML training, Batch inference, Cost-sensitive teams. Its key strengths are very low prices, wide gpu variety, spot instances. 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. 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

TensorDock offers Community → Pro support across 4 regions (US, EU, APAC and 1 more). Runcrate offers Community → Standard support across 4 regions (EU-Central, US, APAC and 1 more). Both providers have comparable region coverage — choose based on which specific regions overlap with your user base or data residency requirements.

Provider background: TensorDock vs Runcrate

TensorDock was founded in 2020 and is headquartered in Boston, MA. Runcrate was founded in 2024 and is headquartered in Berlin, Germany. TensorDock has 4 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.