Specifications Compared
| Spec | GB300 | QUADRO-P5000 |
|---|---|---|
| TDP | 1400W | 180W |
| VRAM | 288 GB | 16 GB |
| Memory Type | HBM3e | GDDR5X |
| Architecture | Blackwell Ultra | Pascal |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 8.9 TFLOPS |
| FP32 Performance | 90 TFLOPS | 8.9 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 288 GB/s |
Performance Analysis
FP16 performance defines modern AI training and inference: the GB300 achieves 2250 TFLOPS compared to the Quadro P5000's 8.9 TFLOPS. This enables the GB300 to process neural network forward and backward passes over 250 times faster, drastically reducing epochs for large language models.
FP32 throughput reveals simulation disparities: 90 TFLOPS on GB300 versus 8.9 TFLOPS on P5000 supports complex physics or rendering at scales unattainable on older hardware. Memory bandwidth amplifies this: 12000 GB/s on GB300 permits batch sizes exceeding hundreds of sequences, minimizing data starvation in training, while 288 GB/s on P5000 limits batches to small datasets.
Power efficiency contextualizes deployment: GB300's 1400W TDP suits rack-scale clusters with NVSwitch and NVLink interconnects, whereas P5000's 180W fits PCIe slots in low-density environments. These specs position GB300 for exabyte-scale AI and P5000 for legacy tasks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Quadro P5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | Amsterdam | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro P5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.78/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.78/GPU/hr | Available |
When to Choose the GB300 SXM6
Data center operators select the GB300 for LLM training or inference on models exceeding 100 billion parameters, leveraging 288 GB HBM3e VRAM and 12000 GB/s bandwidth to handle massive contexts without multi-GPU sharding. FP8 performance at 4500 TFLOPS accelerates quantized inference in production hyperscalers.
Scientific simulations requiring 90 TFLOPS FP32, such as climate modeling, favor GB300's SXM form factor and NVLink for seamless multi-node scaling.
When to Choose the Quadro P5000
Budget-conscious users choose the Quadro P5000 for CAD workflows or light visualization, where 16 GB GDDR5X suffices and $0.78 per hour pricing across six cloud offers minimizes costs. Its 180W TDP enables deployment in standard PCIe servers without specialized cooling.
Legacy software tied to Pascal drivers benefits from P5000's availability, avoiding recompilation for newer architectures.
Use Cases
GB300's 288 GB HBM3e VRAM and 12000 GB/s bandwidth support massive datasets and large batch sizes for billion-parameter models. Quadro P5000's 16 GB GDDR5X cannot accommodate such scales.
FP8 performance of 4500 TFLOPS on GB300 enables high-throughput quantized serving. P5000 lacks comparable tensor core efficiency at 8.9 TFLOPS FP16.
90 TFLOPS FP32 and 2250 TFLOPS FP16 on GB300 accelerate parameter-efficient methods on large models. P5000's identical 8.9 TFLOPS FP16/FP32 proves inadequate for contemporary sizes.
GB300 handles high-resolution generation with 288 GB VRAM for long sequences. P5000's 288 GB/s bandwidth bottlenecks diffusion steps.
GB300's 90 TFLOPS FP32 outperforms P5000's 8.9 TFLOPS for large-scale simulations. NVLink interconnects enable distributed computing unattainable on PCIe-only P5000.
Frequently Asked Questions
What is the VRAM difference between GB300 and Quadro P5000?▾
GB300 provides 288 GB HBM3e VRAM, dwarfing Quadro P5000's 16 GB GDDR5X. This enables GB300 to load entire large models in memory. P5000 suits smaller datasets only.
How do memory bandwidths compare?▾
GB300 offers 12000 GB/s, over 41 times the Quadro P5000's 288 GB/s. Higher bandwidth on GB300 supports larger batches in training. P5000 faces data bottlenecks in intensive tasks.
What are the FP16 performance specs?▾
GB300 delivers 2250 TFLOPS FP16 versus Quadro P5000's 8.9 TFLOPS. This gap accelerates AI training on GB300. P5000 remains viable for basic half-precision only.
What is the TDP and form factor difference?▾
GB300 requires 1400W in SXM form with NVSwitch/NVLink, while Quadro P5000 uses 180W in PCIe. GB300 fits data centers; P5000 deploys in workstations.
Is Quadro P5000 available for cloud rental?▾
Quadro P5000 offers start at $0.78 per hour across six providers. GB300 has no live cloud offers currently. P5000 provides immediate low-cost access.
Which GPU has better FP32 performance?▾
GB300 achieves 90 TFLOPS FP32, exceeding Quadro P5000's 8.9 TFLOPS by a factor of 10. GB300 excels in simulations requiring single precision. P5000 handles lighter FP32 loads.
Which is cheaper to rent, the GB300 or the Quadro P5000?▾
Cloud rental prices for both the GB300 and Quadro P5000 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the GB300 have compared to the Quadro P5000?▾
The GB300 has 288 GB of HBM3e memory. The Quadro P5000 has 16 GB of GDDR5X memory.
Can I find GB300 and Quadro P5000 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the GB300 and the Quadro P5000?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the Quadro P5000 uses Pascal (2016). The GB300 delivers 252.8x the FP16 throughput and 41.7x the memory bandwidth of the Quadro P5000.