Provider Comparison

Scaleway vs VERDA

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

Scaleway bills per-hour, while VERDA bills per-hour. Both providers use the same billing granularity, so this factor won't differentiate your decision.

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

Scaleway holds SOC 2, GDPR, ISO 27001 certifications. VERDA holds 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 Scaleway and VERDA 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, Scaleway offers web-based terminal access for quick debugging.

Q: Which provider has better Kubernetes support for orchestration?

Both Scaleway and VERDA support Kubernetes for container orchestration, enabling you to deploy scalable ML pipelines, manage distributed training jobs, and integrate with MLOps tools like Kubeflow. This is essential for teams running production workloads at scale.

Q: What is each provider best suited for?

Scaleway is best suited for European data sovereignty; Integrated cloud services. VERDA excels at Sustainable AI training in Europe. 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 Scaleway and VERDA 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?

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

Q: Which provider has better container and Docker support?

Container support details are not prominently listed for either provider. Check their documentation for Docker and container runtime compatibility.

Q: What unique features differentiate these providers?

Scaleway's standout features include: Nabu AI Supercomputer; Strong environmental credentials. VERDA's standout features include: Use of waste heat for district heating; Green computing focus. These differentiators may be decisive factors depending on your specific technical requirements and workflow preferences.

Scaleway and VERDA are both European GPU cloud providers tailored for AI/ML workloads, but they differ significantly in scope and focus. Scaleway, a major player, emphasizes data sovereignty, offering integrated services like compute, storage, and Kubernetes alongside its Nabu AI Supercomputer—a massive cluster with thousands of H100 and MI300X GPUs for large-scale training. It's ideal for enterprises needing compliance (SOC 2, GDPR, ISO 27001) and broad ecosystem integration. VERDA, conversely, specializes in sustainable computing, repurposing GPU waste heat for district heating, appealing to eco-conscious teams prioritizing green AI in Europe (GDPR, ISO 27001 compliant). Key differentiators include Scaleway's scale and versatility versus VERDA's niche environmental edge. Scaleway suits teams requiring robust multi-region support, high-performance networking, and seamless scaling from experiments to production. VERDA targets sustainability-focused workloads, potentially offering lower carbon footprints but with less emphasis on supercomputing breadth. Both bill per-hour, minimizing short-job costs compared to per-second models elsewhere. Overall, Scaleway provides higher value for production-grade, sovereignty-sensitive deployments, while VERDA excels for green initiatives. ML engineers should weigh infrastructure maturity against ESG goals; Scaleway's Nabu enables exascale ambitions, but VERDA's heat reuse could future-proof sustainable training pipelines. Limited public data on VERDA's GPU fleet size introduces uncertainty, favoring Scaleway for proven reliability. (228 words)

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Our Recommendation

Choose Scaleway for enterprise-scale AI projects demanding data sovereignty, integrated services, and massive GPU clusters like Nabu for LLM training or production inference. It's optimal for mid-to-large teams (10+ engineers) with budgets over €10k/month, needing SOC 2 compliance, low-latency networking, and Kubernetes orchestration. Ideal if technical requirements include multi-GPU scaling across H100/MI300X or hybrid cloud setups. Opt for VERDA when sustainability is paramount, such as EU-funded green AI research or eco-reporting mandates. Best for smaller teams (1-10 engineers) running sustainable training/inference with modest budgets (€1-5k/month), where waste heat reuse offsets environmental impact. Lacks Scaleway's breadth, so avoid if needing supercomputing or extensive compliance. For hybrid needs, start with Scaleway for scale, supplement VERDA for green pilots. Both per-hour billing suits bursty workloads. (142 words)

Live Pricing

Compare real-time GPU offers from Scaleway and VERDA

82 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
QuantaCloud Partner	A100 · H100 / H200 · B200 / B300 32–1024+ GPUs · InfiniBand	∞	Custom configs	Multiple DCs	Reserved / cluster Get a quote in 24h	Available
VERDA	NVIDIA Tesla V100 16GB 16GB VRAM	16GB	6 vCPU 23GB RAM	Finland	$0.14/GPU/hr	Sold Out
VERDA	4×NVIDIA Tesla V100 16GB 16GB VRAM	16GB	20 vCPU 90GB RAM	Helsinki	$0.14/GPU/hr $0.55/hr total (4×)	Sold Out
VERDA	2×NVIDIA Tesla V100 16GB 16GB VRAM	16GB	10 vCPU 45GB RAM	Finland	$0.14/GPU/hr $0.28/hr total (2×)	Sold Out
VERDA	2×NVIDIA Tesla V100 16GB 16GB VRAM	16GB	10 vCPU 45GB RAM	Finland	$0.14/GPU/hr $0.28/hr total (2×)	Sold Out
VERDA	4×NVIDIA Tesla V100 16GB 16GB VRAM	16GB	20 vCPU 90GB RAM	Finland	$0.14/GPU/hr $0.55/hr total (4×)	Sold Out

QuantaCloud

Partner

Available

A100 · H100 / H200 · B200 / B300

32–1024+ GPUs · InfiniBand

Reserved / cluster

Get a quote in 24h

VERDA

Finland

Sold Out

NVIDIA Tesla V100 16GB

16GB VRAM

6 vCPU

23GB RAM

$0.14/GPU/hr

VERDA

Helsinki

Sold Out

NVIDIA Tesla V100 16GB4x

16GB VRAM

20 vCPU

90GB RAM

$0.14/GPU/hr

$0.55/hr total (4×)

VERDA

Finland

Sold Out

NVIDIA Tesla V100 16GB2x

16GB VRAM

10 vCPU

45GB RAM

$0.14/GPU/hr

$0.28/hr total (2×)

VERDA

Finland

Sold Out

NVIDIA Tesla V100 16GB2x

16GB VRAM

10 vCPU

45GB RAM

$0.14/GPU/hr

$0.28/hr total (2×)

VERDA

Finland

Sold Out

NVIDIA Tesla V100 16GB4x

16GB VRAM

20 vCPU

90GB RAM

$0.14/GPU/hr

$0.55/hr total (4×)

View all 82 offers

QuantaCloud

Comparing providers? We broker across all of them.

Stop tab-switching between pricing pages. Tell us what you need — 16+ GPUs, reserved or cluster capacity — and we return one quote at partner rates within 24 hours.

No waitlist24hr quote turnaroundInfiniBand fabric

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

VERDA(Est. 2018)

A provider focused on green computing using waste heat for district heating.

Best For

Sustainable AI training in Europe

Unique Features

Use of waste heat for district heating
Green computing focus

Feature Comparison

Access Methods

Feature	Scaleway	VERDA
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

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

Compliance

Certification	Scaleway	VERDA
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Scaleway	VERDA
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Both Scaleway and VERDA employ per-hour billing for GPUs, contrasting with per-second models from AWS/GCP that favor micro-bursts. This granularity suits ML workloads with 1+ hour jobs but penalizes sub-hour experiments (e.g., quick fine-tunes). Neither prominently features spot instances or reserved contracts in public docs, implying primarily on-demand pricing—Scaleway lists H100s at ~€2.5-4/hour, though VERDA's rates are opaque, likely competitive for green premium. Implications: Per-hour favors long training runs (e.g., days-long LLM pretraining) with predictable costs, but experiment-heavy teams face idle-time waste. Scaleway's integrated billing across services streamlines multi-resource jobs; VERDA's focus may limit discounts. For intermittent use, per-hour edges out per-minute elsewhere, but lacks savings for commitments. Uncertainty on VERDA's full model suggests verifying quotes. (152 words)

Value Assessment

Scaleway delivers superior value for large training runs and production inference, where Nabu's scale enables efficient multi-GPU utilization, amortizing per-hour costs over high throughput (e.g., €/TFLOP competitive with US hyperscalers). Batch inference benefits from integrated storage/networking, reducing overhead. VERDA shines for small experiments and fine-tuning, as green creds justify premiums for ESG-aligned budgets; waste heat reuse indirectly cuts long-run energy costs. However, limited fleet may throttle large-scale value. For real-time inference, Scaleway's maturity wins; VERDA suits if sustainability trumps latency. Overall, Scaleway offers better ROI for >100 GPU-hours/month; VERDA for <50 hours with green mandates. Test via trials due to VERDA opacity. (148 words)

Use Case Comparison

LLM Training

Scaleway recommended

Scaleway

Scaleway excels with Nabu Supercomputer (thousands of H100/MI300X GPUs), enabling distributed training at exascale. Strong multi-node scaling, InfiniBand networking, and sovereignty suit large models. Integrated Object Storage accelerates checkpoints. Proven for production-scale pretraining, though per-hour billing adds up for weeks-long jobs. (68 words)

VERDA

VERDA supports sustainable training via green GPUs, ideal for mid-scale LLMs with waste heat reuse minimizing carbon. Lacks Nabu-scale clusters; suitable for eco-focused runs but uncertain on multi-GPU interconnects or availability. Best for research with ESG reporting, per-hour fits long jobs. Limited details cap massive trainings. (72 words)

Batch Inference

Scaleway recommended

Scaleway

Scaleway's GPU instances with Kubernetes and elastic scaling handle high-volume batches efficiently. Nabu fractions for cost-sharing, fast NVLink for multi-GPU. Integrated services reduce data transfer costs; SOC 2 aids enterprise pipelines. Per-hour viable for scheduled jobs. (64 words)

VERDA

VERDA's green focus suits batch workloads emphasizing sustainability, with per-hour billing for predictable runs. Waste heat offsets energy costs, but unconfirmed autoscaling or storage integration may hinder large batches. Good for EU-compliant, low-volume inference. (62 words)

Real-time Inference

Scaleway recommended

Scaleway

Scaleway offers low-latency GPUs with auto-scaling groups and global edge, plus Nabu for high-throughput serving. Kubernetes support enables serverless-like inference; strong networking ensures <100ms latencies. Ideal for production APIs. (60 words)

VERDA

VERDA provides green inference but lacks detailed low-latency features or edge compute. Per-hour suits steady loads; sustainability appeals for public-facing apps. Uncertain on scaling speed or GPU types for real-time demands. (60 words)

Fine-tuning & Experimentation

Either works

Scaleway

Scaleway supports rapid prototyping with on-demand GPUs, Jupyter integration, and per-hour flexibility. Nabu access for occasional bursts; sovereignty aids sensitive data. Cost-effective for iterations, though minimums apply. (60 words)

VERDA

VERDA's green ethos fits experimental green AI, per-hour ideal for short jobs. Waste heat reuse enhances sustainability narrative for grants. Limited ecosystem may slow workflows; good for small teams prioritizing eco-impact. (61 words)

Technical Comparison

Infrastructure

Scaleway leverages dedicated bare-metal GPU servers (H100, MI300X) with virtualized options, InfiniBand/RoCE networking up to 400Gbps, S3-compatible storage, and managed Kubernetes (Kapsule). Multi-region EU sovereignty. VERDA focuses on green bare-metal GPUs, likely Ethernet-based, with district heating integration; Kubernetes support unclear, storage options basic. Scaleway's maturity enables hybrid workflows; VERDA's niche limits breadth. (98 words)

Performance

Scaleway's Nabu delivers top-tier multi-GPU scaling (GPUDirect, NCCL), high availability for H100 clusters, benchmarking near-native on MI300X. Low inter-node latency suits training. VERDA offers solid green performance but unbenchmarked; potential thermal optimizations from heat reuse, yet smaller fleet risks queuing. Scaleway leads in raw throughput/scale; VERDA for energy efficiency. Verify VERDA GPUs empirically. (92 words)

Frequently Asked Questions

What is the minimum billing increment for each provider?▾

Scaleway bills per-hour, while VERDA bills per-hour. Both providers use the same billing granularity, so this factor won't differentiate your decision.

Which provider has better compliance certifications for enterprise use?▾

Scaleway holds SOC 2, GDPR, ISO 27001 certifications. VERDA holds 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 Scaleway and VERDA 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, Scaleway offers web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Both Scaleway and VERDA support Kubernetes for container orchestration, enabling you to deploy scalable ML pipelines, manage distributed training jobs, and integrate with MLOps tools like Kubeflow. This is essential for teams running production workloads at scale.

What is each provider best suited for?▾

Scaleway is best suited for European data sovereignty; Integrated cloud services. VERDA excels at Sustainable AI training in Europe. 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 Scaleway and VERDA 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?▾

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

Which provider has better container and Docker support?▾

Container support details are not prominently listed for either provider. Check their documentation for Docker and container runtime compatibility.

What unique features differentiate these providers?▾

Scaleway's standout features include: Nabu AI Supercomputer; Strong environmental credentials. VERDA's standout features include: Use of waste heat for district heating; Green computing focus. 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 VERDA, visit https://verda.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.