L40S on Crusoe
Visit CrusoeCrusoe's NVIDIA L40S offering combines a high-performance enterprise GPU with a climate-aligned cloud infrastructure, making it a standout choice for sustainable AI workloads. The L40S, built on NVIDIA's Ada Lovelace architecture, delivers 48GB GDDR6 VRAM, exceptional FP8/INT8 throughput for inference and training, and robust support for visualization, compute, and generative AI tasks. Crusoe powers these GPUs using stranded energy sources, minimizing carbon emissions while providing reliable, scalable HPC. This is ideal for organizations with strict ESG mandates, such as research labs or enterprises prioritizing batch training where environmental impact metrics matter. Key value propositions include per-hour billing with spot instances for cost efficiency, vertically integrated energy-to-cloud operations for low latency, and seamless integration for ML pipelines. ML engineers benefit from the L40S's balanced performance—up to 1.5x faster than A100 in certain V-Ray benchmarks—paired with Crusoe's focus on high-utilization batch jobs, enabling greener, high-throughput AI development without compromising on power or speed. (168 words)
Why NVIDIA L40S on Crusoe?
Choose Crusoe for NVIDIA L40S if sustainability and cost align with your priorities. Crusoe's unique vertically integrated model leverages stranded natural gas for power, slashing carbon footprints by up to 90% compared to traditional grids, perfectly complementing the L40S's energy-efficient Ada architecture. Spot instances enable deep discounts for interruptible batch training, ideal for the GPU's strengths in large-model fine-tuning and inference. Unlike hyperscalers, Crusoe offers predictable per-hour pricing without long-term commitments, and its focus on ESG reporting provides compliance tools for regulated industries. This combo excels for non-real-time workloads, delivering enterprise-grade reliability with lower TCO and environmental impact. (112 words)
Live Pricing
Real-time NVIDIA L40S offers from Crusoe
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Crusoe | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | United States | $0.50/GPU/hr | |||
Crusoe | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | United States | $1.50/GPU/hr |
Performance Notes
On Crusoe, expect NVIDIA L40S to deliver strong performance for AI training and inference, with 48GB VRAM supporting models up to 70B parameters in FP16. Ada Lovelace enables high tensor core throughput (e.g., 1,181 TFLOPS FP8), outperforming A40 in Omniverse and V-Ray by 1.7-2x. Network bandwidth specifics are not publicly detailed but likely 100-400 Gbps InfiniBand/RoCE for multi-GPU scaling; Crusoe supports GPU clusters for distributed training. Storage options include high-IOPS NVMe, suitable for datasets. Multi-GPU efficiency is solid via NVLink, though real-world scaling depends on workload. Limited benchmarks available—performance mirrors datacenter norms, but verify via Crusoe's console for latest. (102 words)
A climate-aligned computing provider powering high-performance computing using stranded energy sources to mitigate environmental impact.
Best For
Unique Features
- Vertically integrated energy-to-cloud model
- Use of stranded energy sources
VRAM
48GB
Architecture
Ada Lovelace
Tier
enterprise
Platform Features
Getting Started
Launching NVIDIA L40S on Crusoe is straightforward via their cloud console or API, optimized for quick setup of sustainable GPU instances. New users can spin up clusters in minutes, with pre-configured ML images for TensorFlow/PyTorch. Focus on spot instances for batch jobs to maximize value. (62 words)
Steps
- 1Sign up at crusoecloud.com and complete ESG-aligned account verification (1-2 minutes).
- 2Navigate to Compute > GPUs, select L40S configuration (e.g., 1-8 GPUs, CPU/RAM).
- 3Choose on-demand or spot pricing, configure storage/network, and select ML Docker image.
- 4Launch instance; SSH or Jupyter access available immediately post-provisioning.
- 5Monitor via dashboard; scale or terminate as needed with auto-billing.
Pro Tips
- Opt for spot instances on L40S for 50-70% savings on batch training; set aggressive bidding for high availability.
- Pre-warm datasets on NVMe storage to leverage L40S's high memory bandwidth for faster epoch times.
- Use Crusoe's carbon tracker API to quantify emissions savings in your ML experiment reports.
Frequently Asked Questions
What is Crusoe's billing model for NVIDIA L40S?▾
Crusoe bills per-hour for GPU instances including NVIDIA L40S. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Crusoe offer spot instances for NVIDIA L40S?▾
Yes, Crusoe 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 Crusoe offer reserved instances for NVIDIA L40S?▾
Yes, Crusoe 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 Crusoe for current reserved pricing and commitment terms.
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