NVIDIA GeForce RTX 3090 Ti vs AMD Instinct MI100
Detailed comparison of specifications, performance, and pricing between NVIDIA GeForce RTX 3090 Ti and AMD Instinct MI100
Difference Analysis
Full Specifications
| Specification | NVIDIA GeForce RTX 3090 Ti | AMD Instinct MI100 |
|---|---|---|
| Brand | NVIDIA | AMD |
| Series | Consumer | Data Center |
| Architecture | Ampere | CDNA |
| VRAM | 24GB | 32GB |
| VRAM Type | GDDR6X | HBM2 |
| Memory Bandwidth | 1.0 TB/s | 1.2 TB/s |
| FP16 TFLOPS | 80.0 | 184.6 |
| Tensor TFLOPS | 320.0 | 184.6 |
| TDP | 450W | 300W |
| Form Factor | - | - |
| Hardware Price | - | - |
| Cloud Price (min) | $0.460/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
NVIDIA GeForce RTX 3090 Ti vs AMD Instinct MI100 FAQ
It depends on your use case. The NVIDIA GeForce RTX 3090 Ti offers 73% better performance (320.0 vs 184.6 TFLOPS). For raw performance, choose NVIDIA GeForce RTX 3090 Ti. For value, consider your budget and workload requirements.
The AMD Instinct MI100 has more VRAM with 32GB compared to 24GB (33% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.
For AI training, the AMD Instinct MI100 is generally better due to its larger VRAM (32GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 24GB, 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.
Upgrading to NVIDIA GeForce RTX 3090 Ti would give you 73% more performance and similar VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.