L4 vs AMD Instinct MI100
Detailed comparison of specifications, performance, and pricing between L4 and AMD Instinct MI100
Difference Analysis
Full Specifications
| Specification | L4 | AMD Instinct MI100 | H100 PCIe | H100 NVL |
|---|---|---|---|---|
| Brand | NVIDIA | AMD | NVIDIA | NVIDIA |
| Series | Data Center | Data Center | Data Center | Data Center |
| Architecture | Ada Lovelace | CDNA | Hopper | Hopper |
| VRAM | 22GB | 32GB | 80GB | 93GB |
| VRAM Type | GDDR6 | HBM2 | HBM2e | HBM3 |
| Memory Bandwidth | 300 GB/s | 1.2 TB/s | 2.0 TB/s | 3.9 TB/s |
| FP16 TFLOPS | 60.6 | 184.6 | 102.0 | 134.0 |
| Tensor TFLOPS | 242.0 | 184.6 | 1.5k | 2.0k |
| TDP | 72W | 300W | 350W | 400W |
| Form Factor | PCIe | - | PCIe | NVL |
| Hardware Price | $$2.8k | - | $$28k | $$35k |
| Cloud Price (min) | $0.032/hr | - | $2.89/hr | $1.33/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
L4 vs AMD Instinct MI100 FAQ
It depends on your use case. The L4 offers 31% better performance (242.0 vs 184.6 TFLOPS). For raw performance, choose L4. For value, consider your budget and workload requirements.
The AMD Instinct MI100 has more VRAM with 32GB compared to 22GB (45% 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 22GB, 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 L4 would give you 31% more performance and similar VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.
