NVIDIA Quadro P4000
1,792
CUDA Cores
8GB
VRAM
243
GB/s
Technical Specifications
1,792
CUDA Cores
1202
Base MHz
1480
Boost MHz
8GB GDDR5
256-bit bus
Performance
5.3
FP32 TFLOPS
10.6
FP16 TFLOPS
105W
TDP
Cloud Availability
0
Available Instances
$0.00/hr
Starting Price
Detailed Specifications
| Architecture | Pascal (Unknown) |
| Release Date | 2017-02-06 |
| Launch Price | $1,199.00 |
| Process | 16nm |
| Transistors | 7.2B |
AI Features
none
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
9.5in
Length
4.4in
Width
1-slot
Height
About Quadro P4000 GPU
The NVIDIA Quadro P4000 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 8GB of VRAM and 1,792 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2017, the Quadro P4000 features Pascal architecture with advanced AI accelerators including Tensor Cores and Transformer Engine support. This makes it ideal for large language models, computer vision tasks, and generative AI applications.
When considering cloud rental options for the Quadro P4000, pricing starts at $0.00/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 243 GB/s enabling fast data transfer for large datasets.
The Quadro P4000 features CUDA compute capability 6.1 and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 16nm manufacturing process ensures efficient power consumption relative to performance output.
External Resources
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
What You Need to Know About the Quadro P4000
Complete Specifications for the NVIDIA Quadro P4000
Get detailed technical specifications for the NVIDIA Quadro P4000 including VRAM capacity of , CUDA core count, Tensor Core count, memory bandwidth, and CUDA compute capability of . This GPU is designed for demanding AI training, inference, and high-performance computing workloads. Understanding these specifications helps you determine whether it is the right fit for PyTorch, TensorFlow, or custom CUDA-based applications.
Compare NVIDIA Quadro P4000 Cloud Rental Prices per Hour
Find the best cloud rental prices for the NVIDIA Quadro P4000 across providers like RunPod, Vast.ai, Lambda Labs, and CoreWeave. GPUvec aggregates real-time pricing data so you can compare costs per hour, find available instances, and choose the most cost-effective provider. GPU cloud pricing for this model varies by region and instance type, so comparing multiple options can save significantly on compute costs.
Is the NVIDIA Quadro P4000 the Right GPU for Your AI Workload?
Learn whether the NVIDIA Quadro P4000 is the right choice for your specific AI and ML workloads. We cover use cases including large language model training, fine-tuning, inference serving, computer vision, scientific computing, and rendering. Compare its specifications and pricing against other GPUs like the H100, A100, and RTX 5090 to make an informed decision for your infrastructure needs.
Top GPUs for Training and Inference
| Category | Rank 1 | Rank 2 | Rank 3 |
|---|---|---|---|
| Best for Training | NVIDIA H200 | NVIDIA H100 | NVIDIA B200 |
| Best for Inference | NVIDIA A40 | NVIDIA A100 | NVIDIA A10 |
Compare GPU specifications and cloud instances to find the best GPU for your workload.