P100 vs AMD Radeon RX 7900 XTX
Detailed comparison of specifications, performance, and pricing between P100 and AMD Radeon RX 7900 XTX
Difference Analysis
Full Specifications
| Specification | P100 | AMD Radeon RX 7900 XTX | H100 | H200 |
|---|---|---|---|---|
| Brand | NVIDIA | AMD | NVIDIA | NVIDIA |
| Series | - | Consumer | Data Center | Data Center |
| Architecture | - | RDNA 3 | Hopper | Hopper |
| VRAM | 16GB | 24GB | 80GB | 141GB |
| VRAM Type | - | GDDR6 | HBM3 | HBM3e |
| Memory Bandwidth | - | 960 GB/s | 3.4 TB/s | 4.8 TB/s |
| FP16 TFLOPS | - | 122.0 | 134.0 | 134.0 |
| Tensor TFLOPS | - | - | 2.0k | 2.0k |
| TDP | - | 355W | 700W | 700W |
| Form Factor | - | - | SXM | SXM |
| Hardware Price | - | - | $$32k | $$38k |
| Cloud Price (min) | $1.46/hr | - | $1.47/hr | $2.30/hr |
Which Should You Choose?
For AI Training
Large model training needs maximum VRAM and memory bandwidth.
For AI Inference
Inference prioritizes throughput and cost efficiency.
Related Comparisons
P100 vs AMD Radeon RX 7900 XTX FAQ
It depends on your use case. The AMD Radeon RX 7900 XTX offers 0% better performance (122.0 vs - TFLOPS). For raw performance, choose AMD Radeon RX 7900 XTX. For value, consider your budget and workload requirements.
The AMD Radeon RX 7900 XTX has more VRAM with 24GB compared to 16GB (50% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the AMD Radeon RX 7900 XTX is generally better due to its larger VRAM (24GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 16GB, the cheaper option may be more cost-effective.
Price comparison requires both GPUs to have available pricing data. Check individual GPU pages for current market prices.
The AMD Radeon RX 7900 XTX actually offers 0% better performance. An "upgrade" to P100 would be a downgrade in raw performance, though it may offer other benefits like lower power consumption or cost.
