Specifications Compared
| Spec | MI325X | V100 |
|---|---|---|
| TDP | 750W | 300W |
| VRAM | 256 GB | 16-32 GB |
| Memory Type | HBM3e | HBM2 |
| Architecture | CDNA 3 | Volta |
| Form Factors | OAM | SXM2, PCIe |
| Interconnect | Infinity Fabric | NVLink, PCIe 3.0 |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 125 TFLOPS |
| FP32 Performance | 1307 TFLOPS | 15.7 TFLOPS |
| FP64 Performance | 40.9 TFLOPS | 7.8 TFLOPS |
| INT8 Performance | 2,614 TOPS | |
| Memory Bandwidth | 6,000 GB/s | 900 GB/s |
Performance Analysis
FP16 performance defines a key advantage for modern AI training: the MI325X delivers 1307 TFLOPS, over 10 times the V100's 125 TFLOPS, enabling faster iterations on large neural networks. FP32 throughput remains balanced on the MI325X at 1307 TFLOPS, far surpassing the V100's 15.7 TFLOPS, which suits simulations requiring full precision. The MI325X also supports FP8 at 2614 TFLOPS, optimizing inference for quantized models unavailable on the V100. Memory bandwidth profoundly affects real-world usage: 6000 GB/s on the MI325X sustains larger batch sizes during training, minimizing I/O bottlenecks, while the V100's 900 GB/s limits scalability for datasets over 32 GB. Higher TDP of 750 W on the MI325X reflects its density, contrasting the V100's efficient 300 W for lighter deployments. These specs translate to the MI325X accelerating inference by handling bigger models in single-GPU configurations.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Tesla V100 32GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Texas | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | New York City | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Texas | $0.29/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | New York City | $0.29/GPU/hr | Available | ||
 Lambda Labs | 8×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 88 vCPU 448GB RAM 6041GB Storage | Texas | $0.79/GPU/hr $6.32/hr total (8×) | Available |
When to Choose the MI325X
The MI325X excels in large-scale LLM training and inference where 256 GB HBM3e VRAM accommodates models beyond the V100's 32 GB limit. Its 6000 GB/s bandwidth supports massive batch sizes, reducing training time via 1307 TFLOPS FP16 performance. Deploy it for cutting-edge research demanding FP8 at 2614 TFLOPS or Infinity Fabric interconnects in AMD clusters.
When to Choose the Tesla V100 32GB
Opt for the V100 in cost-sensitive environments with cloud pricing from $0.29 per hour across 46 offers. Its 300 W TDP fits power-constrained setups, and NVLink or PCIe 3.0 suits legacy CUDA codebases optimized over years. Choose it for lightweight inference or fine-tuning under 32 GB VRAM.
Use Cases
The MI325X's 256 GB HBM3e VRAM handles massive models without sharding, paired with 1307 TFLOPS FP16 for rapid training cycles.
FP8 performance at 2614 TFLOPS and 6000 GB/s bandwidth enable high-throughput serving of large models on a single GPU.
256 GB VRAM supports full-model fine-tuning, with balanced 1307 TFLOPS FP16 and FP32 outperforming the V100's limits.
High memory bandwidth of 6000 GB/s accelerates image generation batches, leveraging 1307 TFLOPS FP16 for faster diffusion steps.
MI325X's 1307 TFLOPS FP32 suits intensive simulations, but V100's 15.7 TFLOPS FP32 works for smaller-scale tasks at lower cost.
Frequently Asked Questions
What is the VRAM capacity of the MI325X versus V100?▾
The MI325X provides 256 GB HBM3e VRAM, eight times the V100 32 GB HBM2. This enables larger models on the MI325X without distributed setups. Bandwidth reaches 6000 GB/s on MI325X against 900 GB/s on V100.
How do FP16 performances compare?▾
MI325X achieves 1307 TFLOPS FP16, over 10 times the V100's 125 TFLOPS. This gap accelerates deep learning training significantly. FP32 on MI325X matches at 1307 TFLOPS versus V100's 15.7 TFLOPS.
What are the power requirements?▾
The MI325X has a 750 W TDP, higher than the V100's 300 W. This supports greater compute density on MI325X. V100 suits lower-power deployments.
Is cloud pricing available for these GPUs?▾
V100 32 GB starts at $0.29 per hour, averaging $1.01 per hour across 46 offers. No live offers exist for MI325X currently. V100 provides immediate accessibility.
What interconnects do they use?▾
MI325X employs Infinity Fabric for AMD scaling. V100 uses NVLink or PCIe 3.0 for NVIDIA clusters. Form factors differ: OAM for MI325X, SXM2 or PCIe for V100.
When was each architecture released?▾
CDNA 3 powers MI325X in 2024, while Volta dates to 2017 for V100. This seven-year gap explains spec advantages like FP8 on MI325X at 2614 TFLOPS.
Which is cheaper to rent, the MI325X or the V100?▾
Cloud rental prices for both the MI325X and V100 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 MI325X have compared to the V100?▾
The MI325X has 256 GB of HBM3e memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find MI325X and V100 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 MI325X and the V100?▾
The MI325X uses the CDNA 3 architecture (2024) while the V100 uses Volta (2017). The MI325X delivers 10.5x the FP16 throughput and 6.7x the memory bandwidth of the V100.