Compute Comparison

Runcrate

GPU Marketplace

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.

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Cheapest On-Demand

$0.170/hr

Cheapest Spot

GPU Listings

7

Billing

On-demand, Spot

Performance Benchmarks

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Provider Info

Headquarters

Berlin, Germany

Founded

2024

Regions

EU-Central, US, APAC, Various

Min Commitment

None

Support

Community → Standard

Strengths

  • 21 GPU types
  • 11 global regions
  • Very competitive pricing
  • Bare metal + VM options

Limitations

  • Marketplace model — hardware quality varies by host
  • No enterprise SLAs or uptime guarantees
  • Not suitable for compliance-sensitive workloads

Best For

Cost-sensitive teamsMulti-region deploymentsWide GPU variety needs

Full GPU Catalog

GPU ModelvRAMOn-DemandSpotAvailabilityRegion
RTX A400016 GB$0.170HighVarious
V100 16GB16 GB$0.430HighVarious
RTX 409024 GB$0.450HighVarious
RTX A600048 GB$0.550HighVarious
A100 80GB80 GB$1.20HighVarious
H100 80GB80 GB$2.08MedVarious
H200 141GB141 GB$8.36LowVarious

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Runcrate GPU pricing overview

Runcrate is a marketplace GPU cloud provider headquartered in Berlin, Germany. 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 is On-demand, Spot with a minimum commitment of None. Available regions include EU-Central, US, APAC, Various. On-demand GPU instances can be provisioned in minutes with no upfront cost, making Runcrate suitable for both short-duration experiments and sustained production workloads.

Runcrate vs other GPU providers

Runcrate competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: 21 GPU types; 11 global regions; Very competitive pricing. Use the side-by-side comparison tool above to see Runcrate pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 7 Runcrate listings alongside 94+ providers in a single sortable view.

Best use cases for Runcrate

Runcrate is best suited for: Cost-sensitive teams, Multi-region deployments, Wide GPU variety needs. Support tiers range from Community → Standard, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 7 active GPU listings on Runcrate, covering RTX A4000, V100 16GB, RTX 4090, RTX A6000 and more. For workloads requiring the highest single-GPU throughput, H100 SXM5 instances with NVLink interconnect deliver the best performance per dollar at scale. For cost-sensitive fine-tuning or inference of models up to 13B parameters, A100 40GB or RTX 4090 instances typically offer the best value.

Runcrate billing model and cost structure

Runcrate uses On-demand, Spot pricing. On-demand instances are billed per second or per hour depending on the instance type, with no termination fees. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing, where available, can reduce costs by 30–60% for predictable long-running workloads. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.

Choosing the right GPU on Runcrate

GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — the 3,350 GB/s HBM3 bandwidth and 989 TFLOPS FP16 throughput make them 2–2.5× faster than A100 for transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB offers the best cost-per-token on most providers. RTX 4090 instances are ideal for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.

How Runcrate pricing data is collected

Prices shown are sourced from Runcrate's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in USD per hour. Daily snapshots are retained for 90 days and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.

Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and 14+ other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.

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Launch your first GPU on Runcrate

On-demand from $0.170/hr — 7 GPU configurations available. On-demand, Spot billing.

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