Quadro P4000 on Paperspace
Visit PaperspacePaperspace's NVIDIA Quadro P4000 offering combines an 8GB Pascal-architecture workstation GPU with the Gradient MLOps platform, making it an accessible entry point for ML engineers, individual developers, and educators tackling visualization, CAD-related AI tasks, or lightweight model training and inference. The P4000, with 1792 CUDA cores and up to 5.3 TFLOPS FP32 performance, excels in professional applications like DCC and rendering, while supporting smaller ML workloads such as prototyping CNNs or running inference on modest datasets. Paperspace's per-second billing minimizes costs for intermittent use, and the Gradient platform streamlines notebook-to-deployment workflows with collaborative notebooks, deployments, and experiments. This combo stands out for its balance of affordability and ease-of-use, ideal for users not requiring high-end datacenter GPUs. Limitations include dated architecture lacking Tensor Cores, capping it at entry-level ML tasks rather than large-scale training.
Why NVIDIA Quadro P4000 on Paperspace?
Choose Paperspace for the Quadro P4000 if you need a cost-effective workstation GPU integrated with a user-friendly MLOps platform. Per-second billing suits bursty prototyping sessions, avoiding hourly commitments common elsewhere. Gradient's seamless notebook-to-deployment pipeline complements the P4000's strengths in visualization and lighter ML, enabling quick iterations without infrastructure management. Paperspace's focus on individuals and education provides intuitive consoles, pre-configured ML environments, and community templates, reducing setup time. The P4000's 8GB VRAM handles moderate datasets effectively on Paperspace's reliable SSD storage and networking, offering better value than on-demand workstation rentals from traditional clouds lacking such ML-specific tooling.
Live Pricing
Real-time NVIDIA Quadro P4000 offers from Paperspace
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
![]() Paperspace | 4×NVIDIA Quadro P4000 8GB VRAM | 8GB | 32 vCPU 120GB RAM 50GB Storage | Amsterdam | $0.51/GPU/hr $2.04/hr total (4×) | Sold Out | ||
![]() Paperspace | 4×NVIDIA Quadro P4000 8GB VRAM | 8GB | 32 vCPU 120GB RAM 50GB Storage | Canada | $0.51/GPU/hr $2.04/hr total (4×) | Sold Out | ||
![]() Paperspace | 4×NVIDIA Quadro P4000 8GB VRAM | 8GB | 32 vCPU 120GB RAM 50GB Storage | New York | $0.51/GPU/hr $2.04/hr total (4×) | Sold Out | ||
![]() Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.51/GPU/hr | Available | ||
![]() Paperspace | 2×NVIDIA Quadro P4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.51/GPU/hr $1.02/hr total (2×) | Available |





Performance Notes
On Paperspace, the Quadro P4000 delivers solid entry-level performance for ML inference, small-batch training, and visualization workloads, with ~5 TFLOPS FP32 and 8GB GDDR5 VRAM supporting models up to ~4-6GB. Expect 1-10 Gbps networking suitable for data loading, paired with NVMe SSDs for fast I/O. No native multi-GPU scaling for this tier; it's single-GPU only. Pascal lacks Tensor Cores, so FP16/INT8 efficiency lags modern GPUs, but CUDA 11+ compatibility aids legacy code. Real-world benchmarks show 2-3x slower training vs. RTX 30-series for ResNet-like tasks; user reports confirm reliability for Jupyter-based prototyping, though sustained loads may throttle without premium cooling data.
A provider offering the Gradient MLOps platform for simplifying notebook-to-deployment workflows.
Best For
Unique Features
- Gradient platform for ML workflows
VRAM
8GB
Architecture
Pascal
Tier
workstation
Platform Features
Getting Started
Launching a Quadro P4000 instance on Paperspace is straightforward via the web console or Gradient platform. Sign up for a free account, select the P4000 machine type, and access pre-built ML environments with JupyterLab for immediate prototyping.
Steps
- 1Create a Paperspace account and add payment method for per-second billing.
- 2Navigate to 'Machines' or Gradient console and select Quadro P4000 instance type.
- 3Choose OS/image (e.g., PyTorch or TensorFlow template) and storage size.
- 4Click 'Create' to launch; wait 1-2 minutes for readiness.
- 5Connect via browser Jupyter, SSH, or VNC from the console dashboard.
Pro Tips
- Leverage Gradient notebooks for collaborative ML workflows and auto-save experiments to avoid data loss on short sessions.
- Monitor usage in real-time via the billing dashboard to optimize per-second costs for bursty prototyping.
- Pre-load datasets to attached storage before heavy training to maximize the P4000's VRAM for compute.
Frequently Asked Questions
What is Paperspace's billing model for NVIDIA Quadro P4000?▾
Paperspace bills per-second for GPU instances including NVIDIA Quadro P4000. 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 Paperspace offer spot instances for NVIDIA Quadro P4000?▾
No, Paperspace does not currently offer spot instances for NVIDIA Quadro P4000. 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.
How can I access NVIDIA Quadro P4000 instances on Paperspace?▾
Paperspace provides access to NVIDIA Quadro P4000 instances via SSH, built-in Jupyter notebooks, web-based terminal, Docker containers. The built-in Jupyter notebook support makes it easy to start experimenting immediately without additional setup. SSH access gives you full control over the instance for custom configurations and production deployments.
What compliance certifications does Paperspace have for NVIDIA Quadro P4000 workloads?▾
Paperspace maintains SOC 2, GDPR certifications, making it suitable for regulated workloads. SOC 2 certification demonstrates strong security controls for handling sensitive data. Contact Paperspace directly for detailed compliance documentation and BAA agreements if needed.
Can I use NVIDIA Quadro P4000 with Kubernetes on Paperspace?▾
Paperspace does not prominently advertise native Kubernetes support. You may need to manage your own Kubernetes cluster or use alternative orchestration methods. However, they do support Docker containers, which can be a stepping stone to container orchestration.
What are the specifications of the NVIDIA Quadro P4000?▾
The NVIDIA Quadro P4000 features 8GB of high-bandwidth memory, built on NVIDIA's Pascal architecture. As a workstation-class GPU, it's well-suited for professional visualization, rendering, and medium-scale ML tasks. It offers a good balance of performance and cost for development and smaller production workloads.
What workloads is NVIDIA Quadro P4000 on Paperspace best suited for?▾
The NVIDIA Quadro P4000 on Paperspace is well-suited for model development, fine-tuning, medium-scale training, and inference workloads. Paperspace specifically excels at: Individual developers and education. Consider your model size, training data volume, and latency requirements when evaluating this combination for your specific use case.
Does Paperspace offer reserved instances for NVIDIA Quadro P4000?▾
Yes, Paperspace offers reserved instance pricing for NVIDIA Quadro P4000, 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 Paperspace for current reserved pricing and commitment terms.
What unique features does Paperspace offer for NVIDIA Quadro P4000?▾
Paperspace differentiates itself with: Gradient platform for ML workflows. These features may provide advantages depending on your specific workflow requirements and technical needs. Evaluate how these capabilities align with your ML infrastructure goals when making your decision.
How do I get started with NVIDIA Quadro P4000 on Paperspace?▾
To get started with NVIDIA Quadro P4000 on Paperspace, visit https://www.paperspace.com?utm_source=gpuperhour&utm_medium=referral to create an account. Most providers offer a straightforward signup process, and some provide initial credits for new users. Once registered, you can typically launch a NVIDIA Quadro P4000 instance within minutes through their dashboard or API. We recommend starting with a small experiment to familiarize yourself with the platform before scaling up to larger workloads.
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