H200 SXM
LLM inference · fine-tuning
$1,832/ 30 days
View GPU H200 SXM vs MI300X
Compare memory, node configurations, and fixed weekly and monthly cost before choosing between NVIDIA H200 SXM and AMD Instinct MI300X.
MI300X provides 51 GB more VRAM per card. MI300X costs $560 less per 30-day term . Choose based on whether memory headroom or lower fixed cost is the binding constraint.
LLM inference · fine-tuning
large models · ROCm workloads
| Specification | H200 SXM | MI300X |
|---|---|---|
| Architecture | Hopper | CDNA 3 |
| VRAM | 141 GB HBM3e | 192 GB HBM3 |
| Host resources / card | 24 vCPU · 192 GB RAM | 28 vCPU · 256 GB RAM |
| Local NVMe / card | 3.84 TB | 3.84 TB |
| 7-day price / card | $512 | $360 |
| 30-day price / card | $1,832 | $1,272 |
| 4-GPU node / 30 days | $6,742 | $4,681 |
| Catalog quantity | 265 cards | 430 cards |
Workload decision · updated 2026-09-04
H200 offers 141 GB on the Hopper CUDA platform; MI300X offers 192 GB on AMD’s ROCm platform. More memory can simplify the model layout, while retaining an already-qualified software stack can reduce migration work.
Choose H200 when the application depends on CUDA-only extensions, Hopper-validated containers or NVIDIA libraries that have not been qualified on ROCm. The larger memory capacity relative to an 80 GB card may reduce the need for sharding.
Choose MI300X when 192 GB can avoid a multi-GPU split and the complete workload has passed testing on ROCm. Validate the serving or training backend, custom operations, attention kernels and quantization format, not just a successful PyTorch import.
| Manufacturer specification | H200 SXM | MI300X |
|---|---|---|
| Architecture | NVIDIA Hopper | AMD CDNA 3 |
| Memory | 141 GB HBM3e | 192 GB HBM3 |
| Published memory bandwidth | 4.8 TB/s | 5.3 TB/s peak theoretical |
| Primary software stack | CUDA | ROCm |
| Reference accelerator fabric | NVLink in HGX systems | Infinity Fabric in MI300X platforms |
Published accelerator specifications, not a measurement of AnchorGPU infrastructure. Host topology and delivered fabric must be confirmed separately.
Bottom line. Prefer H200 for CUDA-dependent continuity. Evaluate MI300X when a validated ROCm path and larger single-accelerator memory reduce your application’s complexity.
Catalog cost difference: $152 per 7 days and $560 per 30 days. Prices are read from the same catalog as the configurator.
Manufacturer specifications inform the comparison. Recommendations are workload-dependent; no AnchorGPU performance benchmark is claimed.
NVIDIA H200 specifications ↗AMD MI300X specifications ↗PyTorch on ROCm ↗