A40 on LeaderGPU
Visit LeaderGPULeaderGPU provides the NVIDIA A40 GPU on bare-metal servers, delivering 48GB GDDR6 VRAM and Ampere architecture optimized for enterprise workloads like professional visualization, rendering, compute-intensive simulations, and AI/ML training. This combination stands out for ML engineers seeking high-performance, low-latency GPU access without virtualization overhead, leveraging LeaderGPU's high-bandwidth networking and diverse GPU portfolio. Ideal for data scientists handling large-scale models, inference pipelines, or rendering tasks, it offers robust tensor core performance (up to 74.8 TFLOPS FP16) and RT cores for ray-tracing accelerated workflows. Key value propositions include flexible per-minute billing alongside weekly/monthly flat rates for cost predictability on long-running jobs, high-speed storage options, and bare-metal reliability minimizing latency. While best known for hash cracking and rendering, the A40's capabilities extend effectively to medium-to-large ML models, making this a noteworthy option for performance-focused teams evaluating GPU cloud providers.
Why NVIDIA A40 on LeaderGPU?
Choose LeaderGPU for NVIDIA A40 when prioritizing bare-metal performance with high-bandwidth interconnects (up to 100Gbps+ networking) that maximize the GPU's 48GB VRAM for memory-intensive ML tasks like fine-tuning LLMs or generative AI. LeaderGPU's strengths in diverse GPUs and flat-rate billing (weekly/monthly) complement A40's sustained compute prowess, offering cost efficiency for rendering or training bursts without hourly lock-in. Per-minute granularity suits variable workloads, while bare-metal eliminates hypervisor overhead, ensuring full PCIe 4.0 x16 bandwidth. This setup excels over virtualized alternatives for latency-sensitive applications, though ML-specific optimizations like pre-installed CUDA may vary—confirm via their dashboard for seamless integration.
Live Pricing
Real-time NVIDIA A40 offers from LeaderGPU
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 8×NVIDIA A40 48GB VRAM | 48GB | 48 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.52/GPU/hr $4.13/hr total (8×) | Available |
Performance Notes
On LeaderGPU, expect strong A40 performance with bare-metal delivering full 10,752 CUDA cores, 6912 tensor cores, and 48GB VRAM at PCIe 4.0 speeds. High-bandwidth networks (100Gbps+) support distributed training, but multi-GPU scaling via NVLink depends on config—single A40 setups shine for single-node tasks. Storage is NVMe-based SSDs for fast I/O, aiding data loading in ML pipelines. Benchmarks suggest 35.6 TFLOPS FP32, competitive for inference/rendering; ML throughput (e.g., ResNet-50) aligns with datacenter norms. Unknowns include exact interconnect topology or pre-tuned ML frameworks—test via short deployments. Limitations: not optimized for ultra-scale clusters like H100 pods.
A provider specializing in bare-metal servers with high bandwidth and diverse GPU availability.
Best For
Unique Features
- Flexible weekly/monthly flat-rate billing
- Diverse consumer GPU cards
VRAM
48GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Launching NVIDIA A40 on LeaderGPU is straightforward via their web dashboard, emphasizing bare-metal simplicity. New users benefit from quick per-minute provisioning, ideal for ML prototyping or rendering jobs. Expect SSH/root access post-deploy for custom CUDA/Docker setups.
Steps
- 1Create account on LeaderGPU.com and verify payment method.
- 2Navigate to GPU catalog, select NVIDIA A40 bare-metal config.
- 3Choose storage/RAM/network options and billing (per-min/weekly/monthly).
- 4Click deploy; instance ready in 5-10 minutes with IP/credentials.
- 5SSH in, install NVIDIA drivers/CUDA if needed, and launch workloads.
Pro Tips
- Pre-configure Docker images with CUDA 11.8+ for A40 Ampere compatibility to minimize setup time.
- Monitor bandwidth usage for distributed ML; opt for high-RAM configs to leverage full 48GB VRAM.
- Use flat-rate billing for jobs >1 week to optimize costs on sustained training runs.
Frequently Asked Questions
What is LeaderGPU's billing model for NVIDIA A40?▾
LeaderGPU bills per-minute for GPU instances including NVIDIA A40. Check their pricing page for the most current billing details.
Does LeaderGPU offer spot instances for NVIDIA A40?▾
No, LeaderGPU does not currently offer spot instances for NVIDIA A40. 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 LeaderGPU offer reserved instances for NVIDIA A40?▾
Yes, LeaderGPU offers reserved instance pricing for NVIDIA A40, 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 LeaderGPU for current reserved pricing and commitment terms.
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