Provider Comparison

Paperspace vs Scaleway

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

Paperspace bills per-second, while Scaleway bills per-hour. Per-second billing from Paperspace 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?

Paperspace holds SOC 2, GDPR certifications. Scaleway holds SOC 2, GDPR, ISO 27001 certifications. For organizations with strict compliance requirements, Scaleway offers more comprehensive coverage.

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

Both Paperspace and Scaleway 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 Paperspace 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?

Paperspace is best suited for Individual developers and education. Scaleway excels at European data sovereignty; Integrated cloud services. 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?

Both Paperspace and Scaleway offer reserved instance pricing for committed usage, typically providing 20-40% discounts compared to on-demand rates. 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?

Paperspace 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.

Q: What unique features differentiate these providers?

Paperspace's standout features include: Gradient platform for ML workflows. Scaleway's standout features include: Nabu AI Supercomputer; Strong environmental credentials. These differentiators may be decisive factors depending on your specific technical requirements and workflow preferences.

Paperspace and Scaleway represent distinct approaches in the GPU cloud market for ML/AI workloads. Paperspace, with its Gradient MLOps platform, targets individual developers, educators, and small teams seeking seamless notebook-to-production workflows. It excels in simplifying ML pipelines through integrated notebooks, deployments, and monitoring, backed by per-second billing that suits bursty, experimental usage. Compliance includes SOC 2 and GDPR, making it viable for general-purpose ML but less emphasized on sovereignty. Scaleway, a leading European provider, prioritizes data sovereignty and integrated cloud services, ideal for enterprises needing EU-based operations. Its Nabu AI Supercomputer offers massive GPU clusters (e.g., thousands of H100s), strong environmental credentials via renewable energy, and hourly billing optimized for sustained workloads. Broader compliance (SOC 2, GDPR, ISO 27001) supports regulated industries. Key differentiators: Paperspace's developer-friendly Gradient lowers ops overhead for prototyping; Scaleway's scale and sovereignty suit production-scale training and inference in Europe. Paperspace offers agility for solos/small teams; Scaleway provides cost-effective density for large jobs. Value hinges on geography, workflow maturity, and usage patterns—Paperspace for rapid iteration, Scaleway for compliant, high-volume compute. Both deliver NVIDIA GPUs (A100/H100), but Paperspace edges in ease-of-use, while Scaleway leads in cluster interconnects and sustainability. ML engineers should weigh regional needs against tooling simplicity.

Visit Paperspace Visit Scaleway

Our Recommendation

Choose Paperspace for individual developers, students, or small teams (<10) focused on quick experimentation, fine-tuning, or prototyping where per-second billing minimizes costs for short runs (<1 hour) and Gradient streamlines workflows without DevOps expertise. Ideal for US/non-EU users with budgets under $5K/month and no strict sovereignty requirements. Opt for Scaleway when European data residency is mandatory, for mid-to-large teams (10+), or production workloads like large-scale training/inference needing integrated services (e.g., Kubernetes, object storage). Hourly billing favors long jobs (>2 hours), and Nabu clusters excel in multi-node scaling. Suited for budgets $10K+/month prioritizing compliance (ISO 27001), green energy, and cost at scale over per-second flexibility. Hybrid users may start with Paperspace for dev, migrate to Scaleway for prod.

Live Pricing

Compare real-time GPU offers from Paperspace and Scaleway

80 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
Paperspace	NVIDIA Quadro P4000 8GB VRAM	8GB	8 vCPU 30GB RAM 50GB Storage	Amsterdam	$0.51/GPU/hr	Available
Paperspace	NVIDIA Quadro P4000 8GB VRAM	8GB	8 vCPU 30GB RAM 50GB Storage	New York	$0.51/GPU/hr	Available
Paperspace	4×NVIDIA Quadro P4000 8GB VRAM	8GB	32 vCPU 120GB RAM 50GB Storage	Canada	$0.51/GPU/hr $2.04/hr total (4×)	Sold Out
Paperspace	NVIDIA Quadro P4000 8GB VRAM	8GB	8 vCPU 30GB RAM 50GB Storage	Canada	$0.51/GPU/hr	Available
Paperspace	4×NVIDIA Quadro P4000 8GB VRAM	8GB	32 vCPU 120GB RAM 50GB Storage	Amsterdam	$0.51/GPU/hr $2.04/hr total (4×)	Sold Out

Paperspace

Amsterdam

Available

NVIDIA Quadro P4000

8GB VRAM

8 vCPU

30GB RAM

50GB Storage

$0.51/GPU/hr

Paperspace

New York

Available

NVIDIA Quadro P4000

8GB VRAM

8 vCPU

30GB RAM

50GB Storage

$0.51/GPU/hr

Paperspace

Canada

Sold Out

NVIDIA Quadro P40004x

8GB VRAM

32 vCPU

120GB RAM

50GB Storage

$0.51/GPU/hr

$2.04/hr total (4×)

Paperspace

Canada

Available

NVIDIA Quadro P4000

8GB VRAM

8 vCPU

30GB RAM

50GB Storage

$0.51/GPU/hr

Paperspace

Amsterdam

Sold Out

NVIDIA Quadro P40004x

8GB VRAM

32 vCPU

120GB RAM

50GB Storage

$0.51/GPU/hr

$2.04/hr total (4×)

View all 80 offers

Paperspace(Est. 2014)

A provider offering the Gradient MLOps platform for simplifying notebook-to-deployment workflows.

Best For

Individual developers and education

Unique Features

Gradient platform for ML workflows

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

Feature Comparison

Access Methods

Feature	Paperspace	Scaleway
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

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

Compliance

Certification	Paperspace	Scaleway
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Paperspace	Scaleway
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Paperspace employs per-second billing across on-demand (Pro), spot (Core/Garage with up to 90% discounts), and reserved options, enabling precise cost control for variable workloads. No minimums make it ideal for micro-experiments; e.g., A100 at ~$0.99/hour on-demand prorates to pennies for 5-minute jobs. Scaleway uses per-hour billing for on-demand and spot instances (up to 70% off), with commitments for discounts. Minimum 1-hour charge suits steady usage but penalizes interruptions; H100s start ~€2.50/hour on-demand. Paperspace favors intermittent patterns (e.g., daily experiments); Scaleway benefits continuous runs, though spot volatility affects both. No egress fees on Paperspace aid data flows; Scaleway's integrated storage reduces transfer costs in EU.

Value Assessment

Paperspace delivers superior value for small experiments/fine-tuning (e.g., <1 hour jobs save 50-90% vs hourly via per-second/spot). For production inference or batch jobs spanning hours, Scaleway's hourly model and Nabu economies yield better ROI at scale (e.g., multi-GPU clusters cheaper per FLOP). Large LLM training favors Scaleway's cluster pricing; real-time inference suits Paperspace's quick scaling but Scaleway for sustained loads. Budget-conscious solos save with Paperspace (~30% lower for bursty); enterprises gain from Scaleway's sovereignty/compliance without premium. Spot reliability lower on both, but Paperspace's Garage offers persistent cheap storage.

Use Case Comparison

LLM Training

Scaleway recommended

Paperspace

Paperspace supports multi-GPU (up to 8x H100) via Gradient for distributed training, with per-second billing ideal for iterative trials. Easy setup suits small-scale LLMs (<70B params), but limited cluster size caps massive jobs. Strong for teams needing quick checkpointing/storage integration.

Scaleway

Scaleway's Nabu Supercomputer shines with 1000s of H100s interconnected via InfiniBand, enabling efficient large-model training (e.g., 100B+ params). Hourly billing and EU sovereignty fit enterprise-scale, long runs; Kubernetes-native for orchestration.

Batch Inference

Either works

Paperspace

Gradient deployments enable serverless-like batch scaling on GPUs, with per-second efficiency for variable queues. Integrates notebooks for rapid job submission; cost-effective for sporadic high-volume inference via spot instances.

Scaleway

Scaleway offers autoscaling Kubernetes with GPU pools, optimized for batch via integrated Object Storage. Hourly suits predictable loads; Nabu density lowers costs for parallel jobs, enhanced by EU data locality.

Real-time Inference

Paperspace recommended

Paperspace

Paperspace excels with Gradient's one-click deployments for low-latency endpoints, auto-scaling, and per-second billing for traffic spikes. Suits dev/test; persistent volumes aid model serving without overhead.

Scaleway

Scaleway provides managed Kubernetes/Inference endpoints with NVLink for low-latency multi-GPU. Strong for prod with sovereignty; hourly better for steady traffic, integrated monitoring/CDN.

Fine-tuning & Experimentation

Paperspace recommended

Paperspace

Gradient's notebook-to-job workflow is purpose-built, with per-second A100/H100 access and versioning. Perfect for rapid iterations; spot/Core options minimize costs for 10-60min runs common in tuning.

Scaleway

Scaleway supports experimentation via RKE2 Kubernetes and GPUs, but lacks Paperspace's ML-specific UI. Hourly billing works for longer tunes; good for EU-compliant teams with custom pipelines.

Technical Comparison

Infrastructure

Paperspace uses virtualized instances (KVM) with NVIDIA GPUs (A4000 to H100), offering Gradient-managed Kubernetes, block/NVMe storage (up to 8TB), and 100Gbps networking. Focuses on simplicity over bare metal. Scaleway provides bare metal GPUs (A100/H100), virtual instances, and fully managed Kubernetes (Kapsule); Nabu uses custom liquid-cooled racks with InfiniBand/100Gbps Ethernet. Both support EBS-like volumes; Scaleway emphasizes integrated EU storage (BLOCK/Object) and sovereignty zones.

Performance

Both offer A100/H100 with similar single-node perf (e.g., 20-30% H100 uplift). Paperspace scales to 8-GPU nodes effectively for Gradient jobs; multi-node via Slurm/K8s but smaller clusters. Scaleway's Nabu excels in multi-node (1000+ GPUs) with RoCE/IB scaling, lower latency for distributed training (e.g., 1.5x faster Megatron). Availability high on both; Paperspace faster provisioning for small jobs, Scaleway for large reservations. Benchmarks show comparable TFLOPS, but Scaleway greener (100% renewable). Spot interruptions similar.

Frequently Asked Questions

What is the minimum billing increment for each provider?▾

Paperspace bills per-second, while Scaleway bills per-hour. Per-second billing from Paperspace 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?▾

Paperspace holds SOC 2, GDPR certifications. Scaleway holds SOC 2, GDPR, ISO 27001 certifications. For organizations with strict compliance requirements, Scaleway offers more comprehensive coverage.

Which provider offers better development tools like Jupyter notebooks?▾

Both Paperspace and Scaleway 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 Paperspace 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?▾

Paperspace is best suited for Individual developers and education. Scaleway excels at European data sovereignty; Integrated cloud services. 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?▾

Both Paperspace and Scaleway offer reserved instance pricing for committed usage, typically providing 20-40% discounts compared to on-demand rates. 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?▾

Paperspace 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?▾

Paperspace's standout features include: Gradient platform for ML workflows. Scaleway's standout features include: Nabu AI Supercomputer; Strong environmental credentials. 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 Paperspace, visit their website at https://www.paperspace.com?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For Scaleway, visit https://www.scaleway.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.