B300 vs MI300X
Detailed comparison of specifications, performance, and pricing between B300 and MI300X
Difference Analysis
Full Specifications
| Specification | B300 | MI300X | B200 |
|---|---|---|---|
| Brand | NVIDIA | AMD | NVIDIA |
| Series | - | Data Center | Data Center |
| Architecture | - | CDNA3 | Blackwell |
| VRAM | 288GB | 192GB | 192GB |
| VRAM Type | - | HBM3 | HBM3e |
| Memory Bandwidth | - | 5.3 TB/s | 8.0 TB/s |
| FP16 TFLOPS | - | 653.7 | - |
| Tensor TFLOPS | - | - | 4.5k |
| TDP | - | 750W | 1000W |
| Form Factor | - | OAM | SXM |
| Hardware Price | - | $$18k | $$45k |
| Cloud Price (min) | $7.39/hr | $2.39/hr | $3.75/hr |
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B300 vs MI300X FAQ
It depends on your use case. The MI300X offers 0% better performance (653.7 vs - TFLOPS). For raw performance, choose MI300X. For value, consider your budget and workload requirements.
The B300 has more VRAM with 288GB compared to 192GB (50% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the B300 is generally better due to its larger VRAM (288GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 192GB, 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 MI300X actually offers 0% better performance. An "upgrade" to B300 would be a downgrade in raw performance, though it may offer other benefits like lower power consumption or cost.
