Specifications Compared
| Spec | P100 | QUADRO-RTX-8000 |
|---|---|---|
| TDP | 250W | 260W |
| VRAM | 16 GB | 48 GB |
| CUDA Cores | 3,584 | 4,608 |
| Memory Type | HBM2 | GDDR6 |
| Architecture | Pascal | Turing |
| Form Factors | SXM2, PCIe | PCIe |
| Interconnect | NVLink | NVLink |
| FP16 Performance | 9.3 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 9.3 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 4.7 TFLOPS | |
| Memory Bandwidth | 732 GB/s | 672 GB/s |
Performance Analysis
Turing architecture in the Quadro RTX 8000 elevates performance significantly: its 16.3 TFLOPS FP16 and FP32 rates surpass P100's 9.3 TFLOPS by 75 percent, accelerating deep learning training epochs and inference latencies. This delta proves critical for neural network operations where half-precision FP16 dominates modern frameworks, enabling the RTX 8000 to process larger models faster during backpropagation. In inference scenarios, higher throughput reduces per-query times, ideal for high-volume deployments. Memory capacity defines another key disparity: RTX 8000's 48 GB VRAM supports batch sizes up to three times larger than P100's 16 GB limit, minimizing data loading overhead in memory-constrained training runs. Although P100 edges bandwidth at 732 GB/s versus 672 GB/s, the VRAM advantage often outweighs this in VRAM-bound tasks like large language model fine-tuning. Power draw remains close with 260 W TDP for RTX 8000 against 250 W, implying similar cooling demands in clusters.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
P100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 2×NVIDIA Tesla P100 16GB VRAM | 16GB | 0 vCPU 256GB RAM 960GB Storage | Netherlands | $0.60/GPU/hr $1.20/hr total (2×) | Available |
When to Choose the P100
Budget-limited projects favor the P100: its availability from $0.07 per hour makes it viable for prototyping or small-scale compute where 16 GB VRAM suffices. High memory bandwidth of 732 GB/s excels in bandwidth-sensitive simulations, such as certain scientific computing kernels, outperforming RTX 8000's 672 GB/s. Legacy Pascal-optimized software runs natively without recompilation, preserving time for developers tied to older stacks.
When to Choose the Quadro RTX 8000
Workloads demanding extensive memory select the Quadro RTX 8000: 48 GB GDDR6 VRAM handles massive datasets or models exceeding 16 GB, crucial for advanced AI training. Superior 16.3 TFLOPS FP16 and FP32 performance cuts iteration times by 75 percent over P100's 9.3 TFLOPS, boosting productivity in professional visualization pipelines. NVLink interconnect supports multi-GPU scaling effectively in PCIe form factor setups.
Use Cases
Quadro RTX 8000's 48 GB VRAM accommodates large language models during training, preventing out-of-memory errors common with P100's 16 GB limit. Its 16.3 TFLOPS FP16 performance also speeds up gradient computations by 75 percent.
Smaller models fit P100's 16 GB VRAM with 732 GB/s bandwidth aiding quick data throughput. Larger deployments leverage RTX 8000's 48 GB and 16.3 TFLOPS for higher concurrency.
RTX 8000's 48 GB VRAM supports bigger batch sizes in fine-tuning, reducing epochs needed. 16.3 TFLOPS FP32 throughput accelerates parameter updates over P100's 9.3 TFLOPS.
Image generation demands high VRAM for high-resolution outputs: RTX 8000's 48 GB enables larger latents than P100's 16 GB. Enhanced 16.3 TFLOPS FP16 halves diffusion step times.
P100's 732 GB/s bandwidth excels in memory-intensive simulations like molecular dynamics. Lower $0.07 per hour cost suits prolonged runs without RTX 8000's VRAM excess.
Frequently Asked Questions
Which GPU has more VRAM, P100 or Quadro RTX 8000?▾
The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, tripling the P100's 16 GB HBM2 capacity. This makes RTX 8000 preferable for memory-heavy tasks. P100 suffices for lighter workloads.
How do FP32 performance levels compare between P100 and RTX 8000?▾
RTX 8000 achieves 16.3 TFLOPS FP32, 75 percent higher than P100's 9.3 TFLOPS. This boosts single-precision computations in simulations. Training benefits most from the uplift.
What is the memory bandwidth difference?▾
P100 leads with 732 GB/s from HBM2, exceeding RTX 8000's 672 GB/s GDDR6. Bandwidth-bound apps favor P100. VRAM size often dominates in AI.
Are both GPUs available on cloud platforms?▾
P100 lists from $0.07 per hour across three providers, averaging $0.25 per hour. RTX 8000 has no live offers currently. Check gpuperhour.com for updates.
Do P100 and RTX 8000 support NVLink?▾
Both include NVLink interconnect for multi-GPU communication. P100 offers SXM2 or PCIe forms, RTX 8000 uses PCIe. This enables efficient scaling in clusters.
Which has lower power consumption?▾
P100 draws 250 W TDP, slightly under RTX 8000's 260 W. Differences minimize in dense racks. Performance per watt favors RTX 8000 at 16.3 TFLOPS.
Which is cheaper to rent, the P100 or the Quadro RTX 8000?▾
Cloud rental prices for both the P100 and Quadro RTX 8000 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 P100 have compared to the Quadro RTX 8000?▾
The P100 has 16 GB of HBM2 memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.
Can I find P100 and Quadro RTX 8000 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 P100 and the Quadro RTX 8000?▾
The P100 uses the Pascal architecture (2016) while the Quadro RTX 8000 uses Turing (2018). The Quadro RTX 8000 delivers 1.8x the FP16 throughput and 1.1x the memory bandwidth of the P100.