MI300 vs GH200

Detailed comparison of specifications, performance, and pricing between AMD Instinct MI300 and GH200

🏆
Overall Winner
MI300
Wins 4 of 7 categories
Performance Leader
MI300
490.3 TFLOPS (+0%)

Difference Analysis

Metric
MI300
Difference
GH200
Tensor TFLOPS
490.3
=
-
VRAM
128GB
+33%
96GB
Memory Bandwidth
5.3 TB/s
=
-
Hardware Price
$$15k
=
-
Cloud Price/hr
-
=
$1.49

Full Specifications

Specification MI300 GH200
Brand AMD NVIDIA
Series Data Center -
Architecture CDNA3 -
VRAM 128GB 96GB
VRAM Type HBM3 -
Memory Bandwidth 5.3 TB/s -
FP16 TFLOPS 490.3 -
Tensor TFLOPS - -
TDP 750W -
Form Factor OAM -
Hardware Price $$15k -
Cloud Price (min) - $1.49/hr

Which Should You Choose?

🧠

For AI Training

Large model training needs maximum VRAM and memory bandwidth.

Recommended: MI300
128GB VRAM · 5.3 TB/s

For AI Inference

Inference prioritizes throughput and cost efficiency.

Recommended: MI300
Best performance per dollar

MI300 vs GH200 FAQ

It depends on your use case. The MI300 offers 0% better performance (490.3 vs - TFLOPS). For raw performance, choose MI300. For value, consider your budget and workload requirements.

The MI300 has more VRAM with 128GB compared to 96GB (33% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.

For AI training, the MI300 is generally better due to its larger VRAM (128GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 96GB, 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 MI300 would give you 0% more performance and 33% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.