A40 on TensorDock
Visit TensorDockTensorDock offers the NVIDIA A40 GPU with 48GB of VRAM for cloud-based machine learning and AI workloads. This enterprise-tier GPU based on the Ampere architecture provides the compute power needed for training and inference tasks. TensorDock's platform allows you to provision NVIDIA A40 instances on-demand, scaling resources based on your project requirements. Whether you're fine-tuning models, running batch inference, or developing new ML applications, this GPU option provides professional-grade compute accessible through the cloud.
Why NVIDIA A40 on TensorDock?
Choosing NVIDIA A40 on TensorDock gives you access to enterprise-grade GPU compute through TensorDock's cloud infrastructure. The availability of spot instances can significantly reduce costs for flexible workloads. This combination is suitable for teams looking for 48GB of GPU memory without managing physical hardware.
Live Pricing
Real-time NVIDIA A40 offers from TensorDock
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Detroit, Michigan | $0.08/GPU/hr | Sold Out | ||
TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.09/GPU/hr | Sold Out | ||
TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.09/GPU/hr | Sold Out | ||
TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Rzeszow, Subcarpathian | $0.10/GPU/hr | Sold Out | ||
TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Raleigh, North Carolina | $0.11/GPU/hr | Sold Out |
Performance Notes
The NVIDIA A40 delivers high-end performance for ML workloads. With 48GB VRAM, it can handle large language models and extensive batch sizes. Actual performance will depend on your specific workload, data pipeline efficiency, and how well your code utilizes the GPU.
A GPU marketplace offering extremely low spot prices, stabilized by acquisition by Voltage Park.
Best For
Unique Features
- Marketplace model
- Stabilized inventory post-acquisition
VRAM
48GB
Architecture
Ampere
Tier
enterprise
Platform Features
Getting Started
Getting started with NVIDIA A40 on TensorDock involves creating an account, selecting your instance configuration, and launching your GPU instance. Most users can have a NVIDIA A40 instance running within minutes of signup.
Steps
- 1Visit https://tensordock.com?utm_source=gpuperhour&utm_medium=referral and create an account
- 2Complete account verification and add a payment method
- 3Browse available GPU instances and select NVIDIA A40
- 4Configure your instance (OS, storage, networking)
- 5Launch the instance and connect via SSH or web interface
Pro Tips
- Check current availability before planning large-scale deployments
- Use spot instances for significant cost savings on interruptible workloads
- Start with a small test workload to verify compatibility with your code
Frequently Asked Questions
What is TensorDock's billing model for NVIDIA A40?▾
TensorDock bills per-second for GPU instances including NVIDIA A40. 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 TensorDock offer spot instances for NVIDIA A40?▾
Yes, TensorDock offers spot/preemptible instances for NVIDIA A40, 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.
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