MI300X vs NVIDIA H200 NVL

Detailed comparison of specifications, performance, and pricing between AMD Instinct MI300X and NVIDIA H200 NVL

🏆
Overall Winner
MI300X
Wins 5 of 7 categories
Performance Leader
MI300X
653.7 TFLOPS (+0%)

Difference Analysis

Metric
MI300X
Difference
NVIDIA H200 NVL
Tensor TFLOPS
653.7
=
-
VRAM
192GB
+34%
143GB
Memory Bandwidth
5.3 TB/s
=
-
Hardware Price
$$18k
=
-
Cloud Price/hr
$1.99
-70%
$3.39

Full Specifications

Specification MI300X NVIDIA H200 NVL
Brand AMD NVIDIA
Series Data Center -
Architecture CDNA3 -
VRAM 192GB 143GB
VRAM Type HBM3 -
Memory Bandwidth 5.3 TB/s -
FP16 TFLOPS 653.7 -
Tensor TFLOPS - -
TDP 750W -
Form Factor OAM -
Hardware Price $$18k -
Cloud Price (min) $1.99/hr $3.39/hr

Which Should You Choose?

🧠

For AI Training

Large model training needs maximum VRAM and memory bandwidth.

Recommended: MI300X
192GB VRAM · 5.3 TB/s

For AI Inference

Inference prioritizes throughput and cost efficiency.

Recommended: MI300X
Best performance per dollar
☁️

For Cloud Rental

Minimize hourly costs for cloud workloads.

Recommended: MI300X
From $1.99/hr

MI300X vs NVIDIA H200 NVL 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 MI300X has more VRAM with 192GB compared to 143GB (34% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.

For AI training, the MI300X 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 143GB, 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 MI300X would give you 0% more performance and 34% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.