Provider Comparison

RunPod vs Scaleway

RunPod and Scaleway represent distinct approaches in the GPU cloud market for ML/AI workloads. RunPod positions itself as a democratized GPU provider, excelling in serverless inference and cost-effective experimentation through its dual-tier model: Community Cloud for shared, low-cost access and Secure Cloud for dedicated hardware. FlashBoot technology enables rapid pod deployment in seconds, ideal for bursty workloads. Billing is per-second with spot instances, minimizing costs for intermittent use. Compliance includes SOC 2, HIPAA, and GDPR, appealing to regulated industries. Scaleway, a European hyperscaler, emphasizes data sovereignty and integrated services, with its Nabu AI Supercomputer offering large-scale GPU clusters. It's best for EU-based teams prioritizing residency and sustainability, backed by strong environmental credentials. Hourly billing suits predictable workloads, with SOC 2, GDPR, and ISO 27001 compliance. Scaleway integrates seamlessly with its broader cloud ecosystem, including object storage and Kubernetes. Key differentiators: RunPod's granular billing and serverless options favor agile experimentation, while Scaleway's sovereignty and scale suit enterprise production. RunPod targets indie devs and startups; Scaleway appeals to EU enterprises needing compliance and integration. Overall, RunPod offers superior flexibility for prototyping, Scaleway better for sovereign, long-running jobs. Choice depends on geography, budget volatility, and scale requirements.

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Our Recommendation

Choose RunPod for cost-sensitive, bursty workloads like experimentation, fine-tuning, or serverless inference, especially with small teams (<10) or budgets under $10k/month. Its per-second billing and spot instances save 50-70% on short runs, with FlashBoot suiting rapid iteration. Ideal for global users without strict EU residency needs. Opt for Scaleway when EU data sovereignty is mandatory, for large-scale training on Nabu clusters, or integrated services (e.g., Kubernetes-orchestrated pipelines). Suited for mid-to-large teams (10+) with steady budgets favoring hourly predictability and sustainability focus. Technical requirements like high-bandwidth EU networking or ISO 27001 favor Scaleway; HIPAA needs point to RunPod. For hybrid needs, start with RunPod for dev/test, migrate to Scaleway for prod.

Live Pricing

Compare real-time GPU offers from RunPod and Scaleway

80 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price
RunPod	NVIDIA RTX A2000 12GB VRAM	12GB	6 vCPU 20GB RAM	🌍global	$0.12/GPU/hr
RunPod	NVIDIA GeForce RTX 3070 8GB VRAM	8GB	6 vCPU 30GB RAM	🌍global	$0.13/GPU/hr
RunPod	NVIDIA RTX A5000 24GB VRAM	24GB	9 vCPU 25GB RAM	🌍global	$0.16/GPU/hr
RunPod	NVIDIA GeForce RTX 3080 10GB VRAM	10GB	8 vCPU 50GB RAM	🌍global	$0.17/GPU/hr
RunPod	NVIDIA RTX A4000 16GB VRAM	16GB	8 vCPU 25GB RAM	🌍global	$0.17/GPU/hr

RunPod

🌍global

NVIDIA RTX A2000

12GB VRAM

6 vCPU

20GB RAM

$0.12/GPU/hr

RunPod

🌍global

NVIDIA GeForce RTX 3070

8GB VRAM

6 vCPU

30GB RAM

$0.13/GPU/hr

RunPod

🌍global

NVIDIA RTX A5000

24GB VRAM

9 vCPU

25GB RAM

$0.16/GPU/hr

RunPod

🌍global

NVIDIA GeForce RTX 3080

10GB VRAM

8 vCPU

50GB RAM

$0.17/GPU/hr

RunPod

🌍global

NVIDIA RTX A4000

16GB VRAM

8 vCPU

25GB RAM

$0.17/GPU/hr

View all 80 offers

RunPod(Est. 2022)

A leader in democratized GPU space offering serverless inference and cost-effective experimentation.

Best For

Serverless inferenceCost-effective experimentation

Unique Features

Dual-tier model (Community vs. Secure)
FlashBoot technology

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	RunPod	Scaleway
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

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

Compliance

Certification	RunPod	Scaleway
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	RunPod	Scaleway
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

RunPod's per-second billing enables precise cost control, charging only for active compute time, with spot instances offering up to 80% discounts versus on-demand. No minimums suit micro-experiments; reserved pods lock rates for longer commitments. This favors variable, short-duration workloads, reducing waste on idle time. Scaleway uses per-hour billing for GPUs, with on-demand and potential reserved options via Nabu, but lacks spot auctions. Minimum 1-hour charges increase costs for sub-hour jobs. Implications: RunPod excels for intermittent use (e.g., 10-min inferences), potentially 3-5x cheaper; Scaleway better for sustained runs (>4 hours) where hourly granularity aligns with steady loads. No public spot for Scaleway limits burst savings; RunPod's model risks interruptions but auto-restarts mitigate this.

Value Assessment

For small experiments (<1 hour), RunPod delivers superior value via per-second/spot, e.g., A100 at ~$0.20-0.50/hr effective vs Scaleway's $1+/hr minimum. Large training runs (>24h) favor Scaleway's predictable hourly rates and Nabu scaling, avoiding spot preemptions. Production inference: RunPod's serverless edges out for variable traffic, autoscaling cost-effectively; Scaleway suits steady loads with integrated services. Overall, RunPod wins for 70% of dev workflows (budget < $5k/mo); Scaleway for enterprise scale (>$20k/mo) needing sovereignty. Factor 20-30% RunPod savings but add 10-20% overhead for spot reliability management.

Use Case Comparison

LLM Training

Scaleway recommended

RunPod

RunPod supports multi-GPU pods up to 8x H100s in Secure Cloud, with spot for cost savings on long runs. FlashBoot deploys clusters quickly, but spot preemptions risk interruptions for days-long jobs. Good for cost-optimized training with manual checkpointing; lacks native large-scale orchestration.

Scaleway

Scaleway's Nabu Supercomputer excels with 100s of GPUs interconnected for massive LLMs, EU sovereignty ensuring data residency. Hourly billing suits extended training; Kubernetes integration aids orchestration. Strong for production-scale without preemption risks.

Batch Inference

RunPod recommended

RunPod

Serverless endpoints scale dynamically per request, per-second billing optimizes sporadic batches. Community tier cheap for testing; Secure for prod. FlashBoot minimizes cold starts, handling variable volumes efficiently without overprovisioning.

Scaleway

Nabu clusters support large batch jobs via Kubernetes, but hourly minimums inflate costs for irregular runs. Integrated storage aids data pipelines; sovereignty benefits regulated batches.

Real-time Inference

Either works

RunPod

Serverless inference shines with auto-scaling, low-latency FlashBoot (<90s deploy), and per-second pay-per-use. Dual-tier allows cheap dev to secure prod transitions; spot viable for non-critical latency.

Scaleway

Dedicate Nabu instances for consistent low-latency, Kubernetes-managed scaling. Hourly billing stable for always-on; EU networking optimizes regional inference but higher base cost.

Fine-tuning & Experimentation

RunPod recommended

RunPod

Per-second/spot ideal for short, iterative runs; quick pod spins test hyperparameters cheaply. Community Cloud accelerates prototyping; Secure for sensitive data.

Scaleway

Hourly suits longer tunes but costlier for failures; Nabu offers scale, Kubernetes streamlines workflows. Sovereignty key for IP-sensitive experiments.

Technical Comparison

Infrastructure

RunPod offers bare-metal-like pods: Community (shared multi-tenant) vs Secure (dedicated single-tenant), with NVLink multi-GPU, 100Gbps networking, and block storage up to 100TB. Supports Docker/Kubernetes via templates; no managed K8s. Scaleway provides virtualized GPUs on Nabu (dedicated clusters), InfiniBand for large-scale, Object/Block storage integration, and managed Kubernetes (Kapsule). RunPod emphasizes isolation tiers; Scaleway focuses on EU-native ecosystem.

Performance

RunPod GPUs (A100/H100) available on-demand, FlashBoot yields <2min boots; multi-GPU scales to 8x with NVLink, but spot variability impacts sustained perf. Scaleway's Nabu boasts 10k+ H100s, InfiniBand >400Gbps for top training throughput; consistent availability but slower provisioning (~hours). RunPod faster for singles; Scaleway superior for distributed jobs. Benchmarks show RunPod competitive on perf/$, Scaleway edges in EU latency.

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

RunPod 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, RunPod would be the better choice.

What is the minimum billing increment for each provider?▾

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

RunPod holds SOC 2, HIPAA, GDPR certifications. Scaleway holds SOC 2, GDPR, ISO 27001 certifications. Both providers have similar compliance postures. Check with each provider directly for the most current certification status and specific compliance documentation.

Which provider offers better development tools like Jupyter notebooks?▾

Both RunPod 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 RunPod 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?▾

RunPod is best suited for Serverless inference; Cost-effective experimentation. 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?▾

Scaleway offers reserved instance pricing for long-term commitments, while RunPod 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?▾

RunPod provides a comprehensive API for programmatic control, while Scaleway may require more manual management. If automation is a priority, RunPod's API support will streamline your infrastructure-as-code workflows.

Which provider has better container and Docker support?▾

RunPod 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?▾

RunPod's standout features include: Dual-tier model (Community vs. Secure); FlashBoot technology. 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 RunPod, visit their website at https://runpod.io/?ref=u7kynjfe&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.