Specifications Compared
| Spec | MI355X | V100 |
|---|---|---|
| TDP | 750W | 300W |
| VRAM | 288 GB | 16-32 GB |
| Memory Type | HBM3e | HBM2 |
| Architecture | CDNA 4 | Volta |
| Form Factors | OAM | SXM2, PCIe |
| Interconnect | Infinity Fabric | NVLink, PCIe 3.0 |
| FP8 Performance | 4,600 TFLOPS | |
| FP16 Performance | 2,300 TFLOPS | 125 TFLOPS |
| FP32 Performance | 2300 TFLOPS | 15.7 TFLOPS |
| FP64 Performance | 72 TFLOPS | 7.8 TFLOPS |
| INT8 Performance | 4,600 TOPS | |
| Memory Bandwidth | 8,000 GB/s | 900 GB/s |
Performance Analysis
FP16 performance dominates modern machine learning training and inference: the MI355X's 2300 TFLOPS vastly outpaces the V100's 125 TFLOPS, enabling faster iterations on large neural networks. The MI355X maintains parity in FP32 at 2300 TFLOPS versus the V100's mere 15.7 TFLOPS, benefiting precision-sensitive scientific simulations. This balanced tensor core scaling reduces precision conversion overheads in mixed workflows.
Memory specifications transform practical usability. The MI355X's 288 GB VRAM supports model sizes and batch dimensions infeasible on the V100's 32 GB limit, such as billion-parameter LLMs without sharding. Bandwidth of 8000 GB/s on the MI355X prevents data starvation in high-throughput scenarios, compared to 900 GB/s on the V100, which constrains larger batch sizes and extends training times.
Power draw reflects these disparities: 750W TDP for the MI355X demands robust cooling, while the V100's 300W suits denser legacy racks.
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 MI355X
The MI355X excels in large-scale AI training and inference where VRAM exceeds 32 GB. Scenarios include deploying models with over 100 billion parameters or processing massive datasets, leveraging 288 GB HBM3e and 2300 TFLOPS FP16. Infinity Fabric interconnect aids multi-GPU scaling for enterprise clusters.
When to Choose the Tesla V100 32GB
The V100 fits budget-conscious deployments with readily available cloud pricing from $0.29 per hour across 46 offers. It suits legacy codebases optimized for Volta or small-to-medium models under 32 GB VRAM, such as fine-tuning with 15.7 TFLOPS FP32. NVLink and PCIe 3.0 ensure compatibility in existing NVIDIA infrastructures.
Use Cases
The MI355X's 288 GB VRAM accommodates massive LLMs without model parallelism, while 2300 TFLOPS FP16 accelerates convergence far beyond the V100's 32 GB and 125 TFLOPS.
High memory bandwidth of 8000 GB/s and 288 GB capacity enable large batch inference on the MI355X. The V100's 900 GB/s and 32 GB limit throughput for production-scale serving.
MI355X handles parameter-efficient fine-tuning on huge models with 2300 TFLOPS FP32. V100's 15.7 TFLOPS FP32 proves inadequate for timely iterations.
V100 suffices for standard Stable Diffusion at 125 TFLOPS FP16 within 32 GB VRAM. MI355X unlocks higher resolutions and batches via 288 GB and 2300 TFLOPS.
MI355X's 2300 TFLOPS FP32 crushes V100's 15.7 TFLOPS for simulations. 288 GB VRAM supports complex datasets unattainable on 32 GB.
Frequently Asked Questions
What is the VRAM difference between MI355X and V100?▾
The MI355X provides 288 GB HBM3e, nine times the V100 32 GB HBM2 capacity. This enables handling vastly larger models or datasets on the MI355X. Legacy applications remain viable on V100's 32 GB.
How do FP16 performances compare?▾
MI355X achieves 2300 TFLOPS FP16, over 18 times the V100's 125 TFLOPS. This gap accelerates deep learning training and inference significantly. FP8 on MI355X reaches 4600 TFLOPS, absent on V100.
What are the memory bandwidth specs?▾
MI355X offers 8000 GB/s, nearly nine times the V100's 900 GB/s. Higher bandwidth reduces bottlenecks in data-intensive tasks. It supports larger batch sizes on MI355X.
How does power consumption differ?▾
MI355X TDP stands at 750W, more than double the V100's 300W. This requires advanced cooling for MI355X deployments. V100 enables higher density in power-limited environments.
What is the cloud pricing for V100?▾
NVIDIA Tesla V100 32GB starts at $0.29 per hour, averaging $1.01 per hour across 46 live offers. MI355X has no live offers currently. V100 provides immediate accessibility.
Which has better FP32 performance?▾
MI355X delivers 2300 TFLOPS FP32, over 146 times the V100's 15.7 TFLOPS. This favors precision workloads on MI355X. V100 suits lighter FP32 tasks.
Which is cheaper to rent, the MI355X or the V100?▾
Cloud rental prices for both the MI355X 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 MI355X have compared to the V100?▾
The MI355X has 288 GB of HBM3e memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find MI355X 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 MI355X and the V100?▾
The MI355X uses the CDNA 4 architecture (2025) while the V100 uses Volta (2017). The MI355X delivers 18.4x the FP16 throughput and 8.9x the memory bandwidth of the V100.