One hour
$2.39
1 GPU × 1h · compute only
AMD ROCm cloud GPU
Rent an AMD Instinct MI300X GPU for AI and HPC.
Direct answer
AMD Instinct MI300X combines CDNA 3, 192 GB of HBM3 and up to 5.3 TB/s of peak memory bandwidth for high-memory AI and HPC workloads. GPURento lists MI300X at $2.39 per GPU-hour in Paris and Frankfurt for teams with a validated ROCm software path.
Reviewed by the GPURento infrastructure team · September 1, 2026
Cost scenarios
What one AMD Instinct MI300X costs at the listed rate.
One day
$57.36
1 GPU × 24h · compute only
Seven days
$401.52
1 GPU × 168h · compute only
Average month · 730h
$1744.70
1 GPU × 730h · compute only
| Memory | 192 GB HBM3 | High-capacity ECC memory documented by AMD. |
|---|---|---|
| Memory bandwidth | Up to 5.3 TB/s | Peak theoretical bandwidth from the manufacturer. |
| Software ecosystem | AMD ROCm | Validate framework, kernel and image compatibility before deployment. |
| On-demand rate | $2.39 / GPU-hour | Current GPURento compute rate before storage and optional services. |
Best for
- Large-model inference under ROCm
- Memory-bound training and fine-tuning
- HPC workloads with validated AMD kernels
- Teams reducing sharding with 192 GB on one GPU
Not the best fit when
- CUDA-only containers or unsupported custom extensions
- Workloads tested only on NVIDIA hardware
- Small jobs that fit a lower-cost 24–48 GB GPU
- Migrations without a ROCm compatibility pilot
Decision method
What to verify before you deploy capacity.
The content below separates published specifications, GPURento catalog references and decisions that still require a workload benchmark.
01
Treat ROCm compatibility as the first gate
MI300X is not a drop-in replacement for every CUDA environment. Confirm the framework version, model runtime, attention kernels, communication library and container image under the intended ROCm release before comparing performance or cost.
- Build or select a ROCm-compatible image
- Run the actual model and custom extensions
- Record correctness before throughput
02
Use 192 GB to reduce unwanted sharding
A larger single-GPU memory pool can simplify model placement, hold more KV cache or reduce parallel overhead. The benefit depends on precision, runtime and traffic shape, so compare the number of GPUs and total cost required by each candidate.
03
Benchmark the complete AMD path
Measure end-to-end time, utilization, memory pressure and output quality with the same data and service target used for NVIDIA comparisons. Peak bandwidth and FLOPS are not substitutes for application results.
Catalog shortlist
Relevant GPU options.
CDNA 3Available
AMD Instinct MI300X
192 GB HBM3 · $2.39/hr
LLM training, inference and HPC under ROCm
EU West · ParisEU Central · Frankfurt
HopperAvailable
NVIDIA H200 SXM
141 GB HBM3e · $3.59/hr
Large-model inference and HPC
EU West · ParisEU Central · Frankfurt
BlackwellAvailable
NVIDIA B200
180 GB HBM3e · $5.98/hr
Frontier training and inference
EU West · ParisEU Central · Frankfurt
AmpereAvailable
NVIDIA A100 80GB
80 GB HBM2e · $1.19/hr
Training, fine-tuning and HPC
EU West · ParisEU Central · Frankfurt
Questions
Clear answers, including the limits.
How much VRAM does an AMD MI300X have?+
AMD specifies 192 GB of HBM3 memory with full-chip ECC and up to 5.3 TB/s of peak theoretical memory bandwidth.
How much does MI300X cloud rental cost?+
The current GPURento catalog rate is $2.39 per MI300X GPU-hour. Storage and optional services are separate.
Can MI300X run CUDA workloads?+
MI300X uses the AMD ROCm ecosystem rather than NVIDIA CUDA. Frameworks and models may support both, but CUDA-only images and extensions need a compatible ROCm implementation or another GPU.
When should I choose MI300X instead of H200?+
MI300X can be attractive when 192 GB of memory and a validated ROCm stack fit the workload. H200 may be simpler for CUDA-first software. Compare end-to-end results on the actual model.
Sources and scope
Last reviewed September 1, 2026. GPURento rates are current catalog references; provisioning state remains visible in the workspace, and manufacturer specifications do not substitute for workload benchmarks.
Continue the research
Deployment plan
Validate the ROCm workload on MI300X.
Create a funded workspace and save the compatible image, region, runtime and storage for a representative benchmark.