Compute Comparison
vs
All providers →

TensorWave vs Runcrate: GPU Compute Price Comparison

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

Provider Overview

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

Strengths & Best For

TensorWave

TensorWave specializes in AMD Instinct MI300X and MI325X GPU instances — the highest-memory GPU accelerators available in any cloud — offering a compelling NVIDIA alternative for large-model LLM inference and distributed AI training via the ROCm ecosystem. On-demand and reserved billing options are available from US-based data centers, with competitive pricing relative to equivalent NVIDIA H100 configurations. The go-to on-demand GPU cloud for teams exploring AMD ROCm or needing massive VRAM for large-context inference.

Strengths
  • AMD MI300X/MI325X
  • Large VRAM options
  • NVIDIA alternative
  • Competitive pricing
Best For
AMD ROCm workloadsLarge-model inferenceNVIDIA-alternative seekers
Visit TensorWave
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

Popular Comparisons

TensorWavespecialist provider

TensorWave specializes in AMD Instinct MI300X and MI325X GPU instances — the highest-memory GPU accelerators available in any cloud — offering a compelling NVIDIA alternative for large-model LLM inference and distributed AI training via the ROCm ecosystem. On-demand and reserved billing options are available from US-based data centers, with competitive pricing relative to equivalent NVIDIA H100 configurations. The go-to on-demand GPU cloud for teams exploring AMD ROCm or needing massive VRAM for large-context inference.

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

TensorWave uses a On-demand, Reserved 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

TensorWave is best suited for: AMD ROCm workloads, Large-model inference, NVIDIA-alternative seekers. Its key strengths are amd mi300x/mi325x, large vram options, nvidia alternative. 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

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

Provider background: TensorWave vs Runcrate

TensorWave was founded in 2023 and is headquartered in Phoenix, AZ. Runcrate was founded in 2024 and is headquartered in Berlin, Germany. TensorWave 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.