B200 vs RTX 4080 Super
Detailed comparison of specifications, performance, and pricing between NVIDIA B200 and NVIDIA GeForce RTX 4080 Super
Difference Analysis
Full Specifications
| Specification | B200 | RTX 4080 Super | AMD Radeon RX 7900 XTX |
|---|---|---|---|
| Brand | NVIDIA | NVIDIA | AMD |
| Series | Data Center | Consumer | Consumer |
| Architecture | Blackwell | Ada Lovelace | RDNA 3 |
| VRAM | 192GB | 16GB | 24GB |
| VRAM Type | HBM3e | GDDR6X | GDDR6 |
| Memory Bandwidth | 8.0 TB/s | 736 GB/s | 960 GB/s |
| FP16 TFLOPS | - | 104.4 | 122.0 |
| Tensor TFLOPS | 4.5k | - | - |
| TDP | 1000W | 320W | 355W |
| Form Factor | SXM | PCIe | - |
| Hardware Price | $$45k | $$1.1k | - |
| Cloud Price (min) | $3.75/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.
On a Budget
Get the most capability for your money.
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B200 vs RTX 4080 Super FAQ
It depends on your use case. The B200 offers 4210% better performance (4.5k vs 104.4 TFLOPS). However, the RTX 4080 Super is 4186% cheaper. For raw performance, choose B200. For value, consider your budget and workload requirements.
The B200 has more VRAM with 192GB compared to 16GB (1100% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the B200 is generally better due to its larger VRAM (192GB). 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.
The RTX 4080 Super is 4186% cheaper at $$1.1k vs $$45k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.
Upgrading to B200 would give you 4210% more performance and 1100% more VRAM. The upgrade cost difference is approximately $$44k. Consider if your workloads are bottlenecked by current GPU capabilities.