RTX A6000 on VERDA
Visit VERDAVERDA provides the NVIDIA RTX A6000, a high-end workstation GPU with 48GB GDDR6 VRAM based on the Ampere architecture, tailored for professional visualization, data science, content creation, and moderate AI/ML workloads. This offering stands out due to VERDA's commitment to green computing, repurposing server waste heat for district heating in Europe, making it a top choice for environmentally conscious ML engineers and data scientists prioritizing sustainability without compromising performance. With per-hour billing, it offers flexibility for short-term projects or prototyping. The RTX A6000 excels in tasks requiring high VRAM, such as large model inference, 3D rendering, and scientific simulations. VERDA's European data centers ensure low-latency access for EU-based teams, compliance with regional data regulations, and reduced carbon footprint compared to traditional providers. Ideal for sustainable AI training and development where ecological impact is a key decision factor, this combo balances professional-grade compute with verifiable green credentials.
Why NVIDIA RTX A6000 on VERDA?
Choose VERDA for the NVIDIA RTX A6000 if sustainability is paramount, as their innovative use of waste heat for district heating minimizes environmental impact—unique among GPU providers. This complements the GPU's workstation strengths in visualization, data science, and VRAM-intensive tasks like fine-tuning medium LLMs or generative AI prototyping. Per-hour billing suits bursty workloads, avoiding long-term commitments. European locations provide low latency for EU users, data sovereignty, and green energy alignment. While not optimized for massive-scale training, this pairing appeals to eco-focused teams leveraging Ampere's RT/Tensor cores efficiently, offering a principled alternative to high-emission hyperscalers.
Live Pricing
Real-time NVIDIA RTX A6000 offers from VERDA
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 VERDA | NVIDIA RTX A6000 48GB VRAM | 48GB | 10 vCPU 60GB RAM | Finland | $0.49/GPU/hr | Sold Out | ||
VERDA | 4×NVIDIA RTX A6000 48GB VRAM | 48GB | 40 vCPU 240GB RAM | Finland | $0.49/GPU/hr $1.96/hr total (4×) | Sold Out | ||
VERDA | 4×NVIDIA RTX A6000 48GB VRAM | 48GB | 40 vCPU 240GB RAM | Finland | $0.49/GPU/hr $1.96/hr total (4×) | Sold Out | ||
VERDA | NVIDIA RTX A6000 48GB VRAM | 48GB | 10 vCPU 60GB RAM | Helsinki | $0.76/GPU/hr | Available | ||
VERDA | 4×NVIDIA RTX A6000 48GB VRAM | 48GB | 40 vCPU 240GB RAM | Helsinki | $0.76/GPU/hr $3.02/hr total (4×) | Available |
Performance Notes
The RTX A6000 on VERDA delivers solid Ampere-era performance for workstation tasks: ~38 TFLOPS FP32, strong RT/Tensor cores for ray tracing and AI inference. Expect reliable single-GPU throughput for data science pipelines, visualization, or models fitting in 48GB VRAM. Network bandwidth, storage (likely NVMe SSDs), and multi-GPU scaling details are not publicly benchmarked—assume standard 10-100Gbps interconnects without NVLink for multi-node. As a workstation-tier offering, it's not for large-scale distributed training; focus on single-instance efficiency. VERDA's green optimizations may introduce minor thermal throttling unknowns, but no reported issues. Test for your workload due to limited independent reviews.
A provider focused on green computing using waste heat for district heating.
Best For
Unique Features
- Use of waste heat for district heating
- Green computing focus
VRAM
48GB
Architecture
Ampere
Tier
workstation
Platform Features
Getting Started
Getting started with VERDA's NVIDIA RTX A6000 is straightforward for ML engineers. Sign up for an account, select the GPU instance via their dashboard, launch with pre-configured images (e.g., Ubuntu with CUDA), and connect via SSH or Jupyter. Per-hour billing starts immediately, ideal for quick prototyping in sustainable environments.
Steps
- 1Create a VERDA account and complete payment setup for per-hour billing.
- 2Navigate to the GPU marketplace and select NVIDIA RTX A6000 instance type.
- 3Choose OS image (e.g., CUDA-enabled Ubuntu) and configure storage/network.
- 4Launch the instance and note the public IP or SSH details.
- 5Connect via SSH, install dependencies (e.g., PyTorch), and verify GPU with nvidia-smi.
Pro Tips
- Leverage 48GB VRAM for memory-bound tasks like Stable Diffusion or large dataset preprocessing to maximize ROI on green compute.
- Monitor VERDA's energy dashboards for waste heat metrics to quantify sustainability in reports or grants.
- Opt for spot instances if available to further reduce costs for non-critical workloads.
Frequently Asked Questions
What is VERDA's billing model for NVIDIA RTX A6000?▾
VERDA bills per-hour for GPU instances including NVIDIA RTX A6000. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does VERDA offer spot instances for NVIDIA RTX A6000?▾
No, VERDA does not currently offer spot instances for NVIDIA RTX A6000. 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 VERDA offer reserved instances for NVIDIA RTX A6000?▾
Yes, VERDA offers reserved instance pricing for NVIDIA RTX A6000, 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 VERDA for current reserved pricing and commitment terms.
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