Provider Comparison

Scaleway vs TensorDock

Q: Which provider offers spot instances for cost savings?

TensorDock offers spot/preemptible instances, which can significantly reduce costs (typically 50-80% off on-demand prices) for interruptible workloads like batch processing and training with checkpoints. Scaleway does not currently offer spot instances, so all usage is billed at on-demand rates. If cost optimization through spot instances is important for your workflow, TensorDock would be the better choice.

Q: What is the minimum billing increment for each provider?

Scaleway bills per-hour, while TensorDock bills per-second. Per-second billing from TensorDock offers better cost efficiency for short experiments and iterative development, as you only pay for exactly what you use.

Q: Which provider has better compliance certifications for enterprise use?

Scaleway holds SOC 2, GDPR, ISO 27001 certifications. TensorDock holds no publicly listed certifications. For organizations with strict compliance requirements, Scaleway offers more comprehensive coverage.

Q: Which provider offers better development tools like Jupyter notebooks?

Both Scaleway and TensorDock offer built-in Jupyter notebook support, making it easy to start experimenting without additional setup. This is particularly valuable for data scientists and researchers who prefer interactive development environments. Additionally, both providers offer web-based terminal access for quick debugging.

Q: Which provider has better Kubernetes support for orchestration?

Scaleway offers native Kubernetes support for container orchestration, while TensorDock does not. If you're building production ML pipelines with Kubernetes-based tools like Kubeflow, Argo, or KServe, Scaleway will integrate more seamlessly with your workflow.

Q: What is each provider best suited for?

Scaleway is best suited for European data sovereignty; Integrated cloud services. TensorDock excels at Extremely low spot prices. Understanding these specializations helps you choose the provider that aligns with your primary use case, though both can handle a variety of GPU computing needs.

Q: Which provider offers reserved instances for long-term savings?

Scaleway offers reserved instance pricing for long-term commitments, while TensorDock does not currently offer this option. Reserved instances are ideal for predictable, steady-state workloads like always-on inference services. For variable workloads, on-demand or spot instances may offer better flexibility.

Q: Which provider offers better enterprise support?

Neither provider prominently advertises enterprise support tiers. Contact each provider directly to discuss custom support arrangements for production deployments.

Q: Which provider has better API and automation support?

Neither provider prominently advertises API access for automation. Check their documentation for programmatic instance management options.

Q: Which provider has better container and Docker support?

TensorDock offers native container support for running Docker images, while Scaleway may require additional configuration. Container support is valuable for reproducible ML pipelines and easy deployment of pre-built environments.

Scaleway and TensorDock represent contrasting approaches in the GPU cloud market for ML/AI workloads. Scaleway, a leading European provider, prioritizes data sovereignty with its Nabu AI Supercomputer, offering integrated services like object storage, Kubernetes, and bare-metal GPUs in GDPR-compliant regions. It's ideal for enterprises needing compliance (SOC 2, ISO 27001) and sustainability, with per-hour billing for predictable costs. Unique strengths include dense GPU clusters (e.g., H100s in Nabu) and environmental credentials from renewable energy usage. TensorDock, post-acquisition by Voltage Park, operates as a GPU marketplace emphasizing ultra-low spot prices via per-second billing. It aggregates inventory from diverse sources, providing spot instances up to 80% cheaper than on-demand, stabilized by improved supply reliability. Best for cost-sensitive users, it suits opportunistic workloads but may face variability in availability and instance types. Key differentiators: Scaleway excels in reliability, integration, and EU residency; TensorDock in raw affordability for interruptible tasks. Scaleway targets regulated industries and production teams valuing uptime; TensorDock appeals to indie ML practitioners, startups, and experimenters chasing savings. Overall, Scaleway offers a premium, sovereign ecosystem (value for compliance-heavy workflows), while TensorDock delivers marketplace agility (value for budget-constrained, flexible scaling). Choice hinges on priorities: sovereignty and integration vs. price and spot economics. Both support NVIDIA GPUs like A100/H100, but Scaleway's Nabu provides purpose-built AI supercomputing at scale.

Visit Scaleway Visit TensorDock

Our Recommendation

Choose Scaleway for production ML workloads requiring data sovereignty, such as EU-regulated enterprises handling sensitive data in finance or healthcare. It's suited for mid-to-large teams (10+ engineers) needing integrated Kubernetes, reliable multi-GPU scaling, and compliance certifications, where per-hour billing ensures cost predictability despite higher base rates. Ideal budgets: $10K+/month with uptime SLAs critical. Opt for TensorDock when budget is paramount for interruptible tasks, fitting solo practitioners, small teams (<5 engineers), or startups running experiments/batch jobs. Per-second spot pricing shines for variable usage, but requires tolerance for interruptions and manual bidding. Best for budgets under $5K/month, non-regulated environments, and workloads migratable on-spot eviction. Avoid TensorDock for latency-sensitive production without failover; Scaleway lacks TensorDock's extreme discounts but offers better long-term ecosystem lock-in.

Live Pricing

Compare real-time GPU offers from Scaleway and TensorDock

80 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.08/GPU/hr	Available
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.08/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Detroit, Michigan	$0.08/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.10/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Rzeszow, Subcarpathian	$0.10/GPU/hr	Sold Out

TensorDock

Tallinn, Harjumaa

Available

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

1000 Mbps ↑

1000 Mbps ↓

$0.08/GPU/hr

TensorDock

Tallinn, Harjumaa

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.08/GPU/hr

TensorDock

Detroit, Michigan

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.08/GPU/hr

TensorDock

Tallinn, Harjumaa

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.10/GPU/hr

TensorDock

Rzeszow, Subcarpathian

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.10/GPU/hr

View all 80 offers

Scaleway(Est. 1999)

A major European cloud provider emphasizing data sovereignty and integrated services.

Best For

European data sovereigntyIntegrated cloud services

Unique Features

Nabu AI Supercomputer
Strong environmental credentials

TensorDock(Est. 2021)

A GPU marketplace offering extremely low spot prices, stabilized by acquisition by Voltage Park.

Best For

Extremely low spot prices

Unique Features

Marketplace model
Stabilized inventory post-acquisition

Feature Comparison

Access Methods

Feature	Scaleway	TensorDock
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	Scaleway	TensorDock
Billing Increment	per-hour	per-second
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	Scaleway	TensorDock
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Scaleway	TensorDock
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Scaleway employs per-hour billing for on-demand GPU instances, with no native spot market but reserved options for discounts on commitments. Pricing starts around €2-5/hour for A100/H100 equivalents in Nabu clusters, emphasizing predictability for sustained runs. No per-second granularity means minimum 1-hour charges, suiting steady workloads but less optimal for short bursts. TensorDock differentiates with per-second billing and a robust spot marketplace, where bids yield instances at $0.20-1.00/hour for H100s (vs. $2-4 on-demand), often 70-80% savings. Post-Voltage Park acquisition, inventory stabilization reduces eviction rates. Spot suits bursty usage; on-demand provides fallback. Implications: TensorDock favors intermittent, cost-optimized patterns (e.g., overnight training), minimizing idle costs; Scaleway better for continuous inference or when billing precision isn't critical, avoiding spot risks like preemption.

Value Assessment

For small experiments (<1 hour), TensorDock dominates with per-second spot pricing, enabling $0.01-0.10 effective costs and pay-per-use efficiency, ideal for rapid prototyping. Large training runs (days-long) favor Scaleway's reliable per-hour rates and Nabu multi-GPU density, avoiding spot evictions that could waste checkpointing; value higher despite 2-3x premiums if uptime >95% required. Production inference: Scaleway wins for steady-state per-hour predictability and integrated autoscaling, better ROI for 24/7 loads. Batch inference: TensorDock excels, leveraging cheap spot capacity for parallel jobs, yielding 3-5x better value if workloads tolerate interruptions via queuing. Overall, TensorDock maximizes value for <50% utilization; Scaleway for high-utilization, compliance-bound scenarios.

Use Case Comparison

LLM Training

Scaleway recommended

Scaleway

Scaleway's Nabu AI Supercomputer provides dense H100 clusters with NVLink for efficient multi-GPU training, integrated Kubernetes for orchestration, and EU sovereignty for data-sensitive models. Per-hour billing suits multi-day runs, with high reliability minimizing restarts. Strong for large-scale pretraining but higher costs limit to budgeted teams.

TensorDock

TensorDock's spot marketplace offers H100s at 70%+ discounts via per-second billing, ideal for cost-cutting long trainings if checkpointing handles evictions. Stabilized inventory post-acquisition improves availability, but variable interconnects may hinder perfect scaling; suits budget-focused runs.

Batch Inference

TensorDock recommended

Scaleway

Scaleway supports scalable batch jobs via integrated Object Storage and Kubernetes, with reliable GPU quotas in sovereign regions. Per-hour model works for scheduled batches, but lacks spot discounts for opportunistic scaling, making it costlier for irregular volumes.

TensorDock

TensorDock shines with ultra-cheap spot instances for parallel batch processing, per-second billing optimizing short-to-medium jobs. Marketplace variety allows bidding on excess capacity, delivering high value despite potential interruptions manageable via job queuing.

Real-time Inference

Scaleway recommended

Scaleway

Scaleway excels with low-latency, always-on instances, autoscaling groups, and integrated load balancers in compliant regions. Nabu GPUs ensure consistent performance for production serving, per-hour billing aligning with steady inference demands.

TensorDock

TensorDock's on-demand options provide inference capacity cheaply, but spot unreliability risks latency spikes unsuitable for real-time SLAs. Per-second helps variable traffic, yet lacks Scaleway's ecosystem for seamless deployment.

Fine-tuning & Experimentation

TensorDock recommended

Scaleway

Scaleway offers flexible GPU access for quick spins-up via console/API, with strong tooling for notebooks and versioning. Compliance aids collaborative teams, but per-hour minimums inflate costs for <1h experiments.

TensorDock

TensorDock's per-second spot pricing is perfect for iterative fine-tuning, enabling dozens of cheap runs on diverse GPUs. Marketplace speed suits rapid testing, though availability hunting adds minor overhead.

Technical Comparison

Infrastructure

Scaleway delivers virtualized and bare-metal GPUs via Nabu, with 400Gbps+ InfiniBand networking, block/object storage integration, and managed Kubernetes (Kapsule) for orchestration. EU data centers ensure sovereignty; supports NVLink for dense clusters. TensorDock's marketplace model aggregates heterogeneous bare-metal/virtual instances from partners, offering varied networking (up to 100Gbps Ethernet/InfiniBand) and storage passthrough. Kubernetes via user-managed; less integrated but flexible across global regions.

Performance

Scaleway's Nabu provides top-tier multi-GPU scaling (e.g., 8x H100 pods with NVLink) and consistent availability, excelling in benchmarked training throughput. TensorDock matches single/multi-GPU perf on H100/A100s but spot evictions disrupt long runs; post-acquisition, uptime improved to ~90%. Scaleway edges in latency-sensitive tasks; TensorDock competitive for cost-per-FLOP in bursts, with noted variability in older inventory.

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

TensorDock offers spot/preemptible instances, which can significantly reduce costs (typically 50-80% off on-demand prices) for interruptible workloads like batch processing and training with checkpoints. Scaleway does not currently offer spot instances, so all usage is billed at on-demand rates. If cost optimization through spot instances is important for your workflow, TensorDock would be the better choice.

What is the minimum billing increment for each provider?▾

Scaleway bills per-hour, while TensorDock bills per-second. Per-second billing from TensorDock offers better cost efficiency for short experiments and iterative development, as you only pay for exactly what you use.

Which provider has better compliance certifications for enterprise use?▾

Scaleway holds SOC 2, GDPR, ISO 27001 certifications. TensorDock holds no publicly listed certifications. For organizations with strict compliance requirements, Scaleway offers more comprehensive coverage.

Which provider offers better development tools like Jupyter notebooks?▾

Both Scaleway and TensorDock offer built-in Jupyter notebook support, making it easy to start experimenting without additional setup. This is particularly valuable for data scientists and researchers who prefer interactive development environments. Additionally, both providers offer web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Scaleway offers native Kubernetes support for container orchestration, while TensorDock does not. If you're building production ML pipelines with Kubernetes-based tools like Kubeflow, Argo, or KServe, Scaleway will integrate more seamlessly with your workflow.

What is each provider best suited for?▾

Scaleway is best suited for European data sovereignty; Integrated cloud services. TensorDock excels at Extremely low spot prices. Understanding these specializations helps you choose the provider that aligns with your primary use case, though both can handle a variety of GPU computing needs.

Which provider offers reserved instances for long-term savings?▾

Scaleway offers reserved instance pricing for long-term commitments, while TensorDock does not currently offer this option. Reserved instances are ideal for predictable, steady-state workloads like always-on inference services. For variable workloads, on-demand or spot instances may offer better flexibility.

Which provider offers better enterprise support?▾

Neither provider prominently advertises enterprise support tiers. Contact each provider directly to discuss custom support arrangements for production deployments.

Which provider has better API and automation support?▾

Neither provider prominently advertises API access for automation. Check their documentation for programmatic instance management options.

Which provider has better container and Docker support?▾

TensorDock offers native container support for running Docker images, while Scaleway may require additional configuration. Container support is valuable for reproducible ML pipelines and easy deployment of pre-built environments.

What unique features differentiate these providers?▾

Scaleway's standout features include: Nabu AI Supercomputer; Strong environmental credentials. TensorDock's standout features include: Marketplace model; Stabilized inventory post-acquisition. These differentiators may be decisive factors depending on your specific technical requirements and workflow preferences.

How do I get started with each provider?▾

To get started with Scaleway, visit their website at https://www.scaleway.com?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For TensorDock, visit https://tensordock.com?utm_source=gpuperhour&utm_medium=referral to sign up. Both providers typically offer some form of free credits or trial period for new users. We recommend starting with a small experiment to evaluate the platform's ease of use, instance launch times, and overall fit for your workflow before committing to larger workloads.