Datacenter AI accelerator with 288 GB HBM3e for large-scale training, LLM inference, and HPC workloads

Rent AMD Instinct MI350X GPUs with reserved pricing. Get datacenter-class AI compute without upfront hardware costs, and scale as your training needs grow.
| MI350X | B200 | % Diff | |
|---|---|---|---|
| Architecture | CDNA 4 | Blackwell | N/A |
| Process Tech | 3 nm | 4 nm | N/A |
| Memory Type | HBM3e | HBM3e | N/A |
| VRAM | 288 GB | 192 GB | +50% |
| Memory Bandwidth | 8 TB/s | ~8 TB/s | ~0% |
| FP8 Performance | ~9.2 PFLOPS | ~9 PFLOPS | ~+2% |
| FP16/BF16 Performance | ~4.6 PFLOPS | ~4.5 PFLOPS | ~+2% |
| TDP | 1 000 W | ~1 000 W | ~0% |
| Interface | OAM / PCIe 5 | NVLink / PCIe 5 | N/A |
| Multi-GPU Interconnect | Infinity Fabric | NVLink 5 | N/A |
| Max GPUs per Node | 8 | 8 | 0% |
| Vendor Ecosystem | ROCm | CUDA | N/A |
With ~9.2 PFLOPS of FP8 matrix performance on CDNA 4, the MI350X delivers datacenter-class AI throughput for large-scale training and inference workloads.
288 GB of HBM3e memory with 8 TB/s bandwidth eliminates memory bottlenecks for the largest foundation models, enabling full-model inference without tensor parallelism.
Built on AMD ROCm, the MI350X supports PyTorch, JAX, and major ML frameworks out of the box — no vendor lock-in, with broad compatibility across AI software stacks.
Train and serve 100B+ parameter LLMs with 288 GB HBM3e — fit entire models on a single accelerator.
Accelerate diffusion models, video generation, and multi-modal AI pipelines at scale.
Run HPC simulations, molecular dynamics, and climate modeling with massive memory and bandwidth.
Serve multiple models or users concurrently with abundant VRAM and high throughput.
Common questions about renting AMD Instinct MI350X GPUs
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