Specifications Compared
| Spec | H100 | MI325X |
|---|---|---|
| TDP | 700W | 750W |
| VRAM | 80-94 GB | 256 GB |
| CUDA Cores | 16,896 | |
| Memory Type | HBM3 | HBM3e |
| Architecture | Hopper | CDNA 3 |
| Form Factors | SXM5, PCIe, NVL | OAM |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | Infinity Fabric |
| Tensor Cores | 528 | |
| FP8 Performance | 3,958 TFLOPS | 2,614 TFLOPS |
| FP16 Performance | 1,979 TFLOPS | 1,307 TFLOPS |
| FP32 Performance | 67 TFLOPS | 1307 TFLOPS |
| FP64 Performance | 34 TFLOPS | 40.9 TFLOPS |
| INT8 Performance | 3,958 TOPS | 2,614 TOPS |
| Memory Bandwidth | 3,350 GB/s | 6,000 GB/s |
Performance Analysis
The FP16 performance gap favors the H100 at 1979 TFLOPS over the MI325X's 1307 TFLOPS, which accelerates mixed-precision training for large language models where FP16 dominates. In contrast, the MI325X's 1307 TFLOPS FP32 dwarfs the H100's 67 TFLOPS, benefiting simulations and scientific computing reliant on single-precision arithmetic. FP8 performance follows suit with H100 at 3958 TFLOPS versus 2614 TFLOPS, enhancing inference throughput for quantized models.
Memory specifications shift the balance: the MI325X's 256 GB HBM3e and 6000 GB/s bandwidth enable larger batch sizes in training, reducing overhead from data loading compared to the H100's 80-94 GB HBM3 at 3350 GB/s. This proves critical for memory-bound inference on models exceeding 100 billion parameters, allowing single-GPU operation where the H100 requires sharding.
Power draw remains close at 700W TDP for H100 and 750W for MI325X, but interconnects differ: H100's NVLink supports faster multi-node scaling than MI325X's Infinity Fabric. Overall, H100 suits compute-intensive tasks, while MI325X excels in capacity-limited scenarios.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
When to Choose the H100
Choose the H100 for workloads demanding immediate availability and superior low-precision compute. Its 1979 TFLOPS FP16 and 3958 TFLOPS FP8 outperform the MI325X, ideal for LLM inference and training where cloud instances start at $0.80 per hour. NVLink interconnect enables efficient multi-GPU setups across SXM5, PCIe, and NVL form factors.
The H100 fits production environments needing proven Hopper architecture performance today, avoiding delays from MI325X's lack of live offers.
When to Choose the MI325X
Select the MI325X for memory-intensive applications leveraging 256 GB HBM3e VRAM and 6000 GB/s bandwidth. This configuration supports massive batch sizes in fine-tuning or scientific simulations, where FP32 at 1307 TFLOPS handles precision-heavy tasks far beyond H100's 67 TFLOPS.
Future deployments benefit from CDNA 3 advancements in OAM form factor with Infinity Fabric, positioning it for single-GPU large model hosting once available.
Use Cases
H100's 1979 TFLOPS FP16 exceeds MI325X's 1307 TFLOPS, accelerating mixed-precision training cycles. Availability across 56 cloud offers ensures immediate deployment.
H100's 3958 TFLOPS FP8 provides superior quantized inference speed over MI325X's 2614 TFLOPS. NVLink supports scalable serving.
MI325X's 256 GB VRAM handles larger models in single GPU, while H100's 1979 TFLOPS FP16 speeds iterations. Choice depends on model size versus compute priority.
H100's FP16 at 1979 TFLOPS and FP8 at 3958 TFLOPS optimize image generation inference. Current pricing from $0.80 per hour fits rapid prototyping.
MI325X's 1307 TFLOPS FP32 vastly outperforms H100's 67 TFLOPS for simulations. 6000 GB/s bandwidth aids data-heavy workloads.
Frequently Asked Questions
Which GPU has more VRAM, H100 or MI325X?▾
The MI325X offers 256 GB HBM3e VRAM, exceeding the H100's 80-94 GB HBM3. This enables larger models on a single MI325X GPU.
How does FP16 performance compare between H100 and MI325X?▾
H100 delivers 1979 TFLOPS FP16, higher than MI325X's 1307 TFLOPS. This advantage suits AI training workloads.
What is the memory bandwidth of these GPUs?▾
MI325X provides 6000 GB/s, surpassing H100's 3350 GB/s. Higher bandwidth reduces bottlenecks in large batch processing.
Is MI325X available in cloud providers now?▾
No live offers exist for MI325X currently. H100 has 56 offers averaging $3.17 per hour from $0.80 per hour.
Which has better FP32 performance?▾
MI325X achieves 1307 TFLOPS FP32, far above H100's 67 TFLOPS. It excels in scientific computing requiring single precision.
What are the TDP ratings?▾
H100 has 700W TDP, while MI325X is at 750W. Both suit high-density data center racks.
Which is cheaper to rent, the H100 or the MI325X?▾
Cloud rental prices for both the H100 and MI325X vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the H100 have compared to the MI325X?▾
The H100 has 80 to 94 GB of HBM3 memory. The MI325X has 256 GB of HBM3e memory.
Can I find H100 and MI325X GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the H100 and the MI325X?▾
The H100 uses the Hopper architecture (2022) while the MI325X uses CDNA 3 (2024). The H100 delivers 1.5x the FP16 throughput and 1.8x the memory bandwidth of the MI325X.