L4 on Scaleway
Visit ScalewayScaleway's NVIDIA L4 offering delivers a compelling European-centric solution for AI inference and media workloads, powered by the Ada Lovelace architecture GPU with 24GB GDDR6 VRAM. This enterprise-tier GPU excels in efficient inference (up to 2.5x better than prior generations on MLPerf benchmarks), video transcoding, and virtual desktops, balancing performance and power efficiency at 72W TDP. Noteworthy for ML engineers seeking GDPR-compliant data sovereignty, Scaleway keeps data in EU regions like Paris and Amsterdam, avoiding US hyperscaler risks. Per-hour billing enables cost-effective, flexible usage for variable workloads. Integration with the Nabu AI Supercomputer allows seamless scaling to larger clusters, while strong environmental credentials from 100% renewable energy match green AI priorities. Target audience: European enterprises, startups, and researchers prioritizing compliance, sustainability, and integrated services over raw training power. Key value: reliable inference at low latency, without vendor lock-in.
Why NVIDIA L4 on Scaleway?
Opt for Scaleway's NVIDIA L4 when EU data sovereignty is non-negotiable—data remains under strict European regulations, ideal for regulated industries. Per-hour billing provides granular cost control for inference-heavy, bursty ML tasks, complementing the L4's power efficiency. Scaleway's infrastructure enhances L4 capabilities with NVMe SSDs for fast data loading, 50-100Gbps networking for low-latency inference serving, and seamless integration with Nabu Supercluster for hybrid scaling. Unique environmental edge: powered by renewables, appealing to sustainable AI initiatives. Avoids hyperscaler premiums and lock-in via open APIs, Terraform support, and Kubernetes compatibility, making it perfect for DevOps-integrated ML pipelines.
Live Pricing
Real-time NVIDIA L4 offers from Scaleway
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Scaleway | 2×NVIDIA L4 24GB VRAM | 24GB | 16 vCPU 96GB RAM | Paris | $0.89/GPU/hr $1.77/hr total (2×) | Sold Out | ||
Scaleway | 4×NVIDIA L4 24GB VRAM | 24GB | 32 vCPU 192GB RAM | Paris | $0.89/GPU/hr $3.54/hr total (4×) | Sold Out | ||
Scaleway | 4×NVIDIA L4 24GB VRAM | 24GB | 32 vCPU 192GB RAM | Warsaw | $0.89/GPU/hr $3.54/hr total (4×) | Sold Out | ||
Scaleway | 8×NVIDIA L4 24GB VRAM | 24GB | 64 vCPU 384GB RAM | Warsaw | $0.89/GPU/hr $7.09/hr total (8×) | Sold Out | ||
Scaleway | NVIDIA L4 24GB VRAM | 24GB | 8 vCPU 48GB RAM | Warsaw | $0.89/GPU/hr | Available |
Performance Notes
Scaleway's L4 instances deliver near-NVIDIA reference performance for inference, e.g., ~300-400 images/sec on ResNet-50 FP16, leveraging Tensor Cores and 4th-gen RT Cores. PCIe 4.0 x16 interface supports multi-GPU scaling via 50-100Gbps RDMA-enabled networking, suitable for distributed serving but less ideal for massive training (prefer H100s). NVMe storage options (up to 30TB local) enable quick dataset access; expect 5-10GB/s throughput. Pre-built CUDA 12.x images accelerate setup. Benchmarks are provider-specific and sparse—real-world perf varies by workload; test with MLPerf. Limitations: no NVLink, so inter-GPU bandwidth caps at network speeds; strong for edge inference, not FP64 compute.
A major European cloud provider emphasizing data sovereignty and integrated services.
Best For
Unique Features
- Nabu AI Supercomputer
- Strong environmental credentials
VRAM
24GB
Architecture
Ada Lovelace
Tier
enterprise
Platform Features
Getting Started
Getting started with Scaleway's NVIDIA L4 is user-friendly via the web console, API, or Terraform. Select from GPU-optimized instances in EU regions, deploy CUDA-ready images, and scale effortlessly. Per-hour billing starts instantly, with SSH/Jupyter access for ML workflows.
Steps
- 1Log in to Scaleway Console and navigate to 'Instances' > 'Create Instance'.
- 2Select 'GPU' tab, choose NVIDIA L4 (24GB), preferred region (e.g., Paris).
- 3Pick Ubuntu 22.04 LTS with CUDA image, configure vCPU/RAM (e.g., 8 vCPU, 32GB).
- 4Add block storage (NVMe), set up SSH key, review per-hour pricing, and launch.
- 5SSH into instance, verify GPU with 'nvidia-smi', install frameworks like PyTorch.
Pro Tips
- Use Scaleway's Flexible Instances for auto-scaling and cost savings on intermittent inference jobs.
- Integrate with RKE2 Kubernetes for multi-GPU orchestration and Nabu House for larger-scale AI.
- Mount Object Storage datasets via s3fs to minimize local SSD usage and egress costs.
Frequently Asked Questions
What is Scaleway's billing model for NVIDIA L4?▾
Scaleway bills per-hour for GPU instances including NVIDIA L4. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Scaleway offer spot instances for NVIDIA L4?▾
No, Scaleway does not currently offer spot instances for NVIDIA L4. All instances are billed at on-demand rates. However, they do offer reserved instances for committed usage, which can provide significant discounts for long-term workloads.
Does Scaleway offer reserved instances for NVIDIA L4?▾
Yes, Scaleway offers reserved instance pricing for NVIDIA L4, which can provide significant discounts (typically 20-40% off on-demand rates) for committed usage periods. Reserved instances are ideal for predictable, long-running workloads like production inference services, ongoing training pipelines, or development environments that run continuously. Contact Scaleway for current reserved pricing and commitment terms.
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