L40S on CoreWeave
Visit CoreWeaveCoreWeave's NVIDIA L40S offering delivers a powerful data center GPU tailored for demanding AI training, inference, visualization, and VFX workloads. Built on the Ada Lovelace architecture with 48GB GDDR6 ECC VRAM, the L40S provides 18,176 CUDA cores, 568 4th-gen Tensor Cores, and up to 91 TFLOPS FP32 performance, striking a balance between high-throughput compute and memory capacity. CoreWeave enhances this with its Kubernetes-native platform, enabling seamless orchestration across massive InfiniBand-backed clusters for scalable multi-GPU deployments. Ideal for sophisticated engineering teams training LLMs at scale or VFX studios needing burst rendering, it stands out for per-second billing, spot instances, and access to hyperscale infrastructure without upfront commitments. Key value propositions include cost efficiency via flexible pricing, low-latency NVLink/InfiniBand interconnects for distributed training, and native support for Kubernetes workflows, making it a go-to for production-grade AI pipelines requiring reliability and elasticity.
Why NVIDIA L40S on CoreWeave?
Choose CoreWeave for NVIDIA L40S when you need Kubernetes-native orchestration paired with enterprise-grade GPUs for AI and VFX. CoreWeave's strengths—massive InfiniBand clusters (up to 400Gb/s+ bandwidth) and hyperscale availability—unlock the L40S's full potential in multi-node training, where low-latency networking accelerates collective operations like AllReduce. Per-second billing and spot instances minimize costs for bursty workloads, complementing the L40S's versatility in FP8/FP16 inference and RTX-enabled rendering. Unlike general clouds, CoreWeave's specialized infrastructure avoids noisy neighbors, ensuring consistent performance for LLM fine-tuning or Omniverse simulations. This combo excels for teams prioritizing scalability, developer velocity via kubectl deployments, and ROI on memory-intensive tasks.
Live Pricing
Real-time NVIDIA L40S offers from CoreWeave
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 CoreWeave | 8×NVIDIA L40S 48GB VRAM | 48GB | 128 vCPU 0GB RAM 7680GB Storage | United States | $2.25/GPU/hr $18.00/hr total (8×) |
Performance Notes
On CoreWeave, expect strong L40S performance: ~91 TFLOPS FP32, 733 TFLOPS FP16 with sparsity, and 1,466 TFLOPS FP8 for inference-heavy AI. 48GB VRAM handles large models like 70B-parameter LLMs in multi-GPU setups. InfiniBand (typically 400-800Gb/s) enables efficient scaling to thousands of GPUs, with Kubernetes pods supporting NVLink for intra-node and NCCL for inter-node comms. Storage via high-IOPS NVMe or distributed filesystems like JuiceFS complements compute. Multi-GPU scaling is excellent for training (e.g., via Ray or Slurm), but exact benchmarks are provider-specific—CoreWeave publishes some H100/L40S perf data, though L40S inference lags behind H100s. Limitations: not top for ultra-scale exascale training; verify cluster availability.
A premier specialized GPU cloud designed for massive-scale AI training and VFX rendering with Kubernetes-native architecture.
Best For
Unique Features
- Kubernetes-native architecture
- Access to massive-scale InfiniBand clusters
VRAM
48GB
Architecture
Ada Lovelace
Tier
enterprise
Platform Features
Getting Started
Getting started with CoreWeave's NVIDIA L40S is straightforward via their web console or kubectl, leveraging Kubernetes for pod deployments. Sign up for an account, fund via credit card or invoice, and launch L40S instances in minutes with pre-built images for PyTorch/TensorFlow.
Steps
- 1Create a CoreWeave account at console.coreweave.com and complete KYC/funding.
- 2Navigate to 'Pods' in the console; select L40S GPU type and configure instance size (e.g., 1-8 GPUs).
- 3Choose image (e.g., CoreWeave PyTorch) and attach storage/network; deploy the pod.
- 4Connect via SSH/Web Terminal or kubectl port-forward once running.
- 5Scale or monitor via Kubernetes dashboard; terminate to stop per-second billing.
Pro Tips
- Use spot instances for non-critical workloads to save up to 70% vs. on-demand, monitoring via console alerts.
- Leverage InfiniBand by requesting high-bandwidth clusters for multi-node training; test NCCL benchmarks early.
- Pre-warm Docker images with NVIDIA drivers/CUDA 12.x for faster launches in production pipelines.
Frequently Asked Questions
What is CoreWeave's billing model for NVIDIA L40S?▾
CoreWeave bills per-second for GPU instances including NVIDIA L40S. Per-second billing ensures you only pay for exactly the compute time you use, which is particularly cost-effective for short experiments, iterative development, and workloads with variable duration.
Does CoreWeave offer spot instances for NVIDIA L40S?▾
Yes, CoreWeave offers spot/preemptible instances for NVIDIA L40S, which can reduce costs by 50-80% compared to on-demand pricing. Spot instances are ideal for fault-tolerant workloads like batch inference, hyperparameter tuning, and training jobs with checkpointing. Note that spot instances can be interrupted when demand is high, so ensure your workflow can handle preemption gracefully.
Does CoreWeave offer reserved instances for NVIDIA L40S?▾
Yes, CoreWeave offers reserved instance pricing for NVIDIA L40S, 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 CoreWeave for current reserved pricing and commitment terms.
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