Specifications Compared
| Spec | MI355X | RTX-5000-ADA |
|---|---|---|
| TDP | 750W | 250W |
| VRAM | 288 GB | 32 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | CDNA 4 | Ada Lovelace |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric | |
| FP8 Performance | 4,600 TFLOPS | |
| FP16 Performance | 2,300 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 2300 TFLOPS | 65.3 TFLOPS |
| FP64 Performance | 72 TFLOPS | |
| INT8 Performance | 4,600 TOPS | 1,044 TOPS |
| Memory Bandwidth | 8,000 GB/s | 576 GB/s |
Performance Analysis
Compute performance defines the core disparity: the MI355X achieves 2300 TFLOPS in FP16 and FP32, enabling rapid training of models with billions of parameters, whereas the RTX 5000 Ada's 65.3 TFLOPS limits it to smaller datasets or lighter workloads. This delta translates to the MI355X completing FP16 matrix multiplications over 35 times faster, ideal for deep learning optimization.
Memory capacity and bandwidth shape real-world usability: 288 GB HBM3e on the MI355X supports batch sizes for models exceeding 100 billion parameters without swapping, while 32 GB GDDR6 on the RTX 5000 Ada restricts to sub-20 billion parameter models. The 8000 GB/s bandwidth versus 576 GB/s prevents bottlenecks in data-heavy inference, allowing larger effective throughputs in transformer-based tasks.
Power and form factor influence deployment: the MI355X's 750W TDP demands robust cooling in OAM racks with Infinity Fabric scaling, contrasting the RTX 5000 Ada's efficient 250W PCIe design for edge or workstation use. FP8 capability at 4600 TFLOPS on MI355X accelerates low-precision inference, unavailable equivalently on RTX 5000 Ada.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the MI355X
The MI355X excels in large-scale AI training and HPC simulations: its 288 GB HBM3e VRAM handles models like 1-trillion-parameter LLMs, and 2300 TFLOPS FP32 compute processes datasets in hours rather than days. Infinity Fabric interconnect supports multi-GPU clusters for distributed training.
Choose MI355X for inference on massive deployments: 4600 TFLOPS FP8 and 8000 GB/s bandwidth sustain high query volumes without latency spikes.
When to Choose the RTX 5000 Ada
The RTX 5000 Ada fits cost-sensitive professional workstations: available from $0.25/hr in cloud, its 32 GB GDDR6 suffices for fine-tuning mid-sized models up to 13 billion parameters at 65.3 TFLOPS FP16.
Opt for RTX 5000 Ada in graphics-heavy tasks or low-power environments: 250W TDP enables deployment in standard PCIe servers without high infrastructure costs.
Use Cases
MI355X's 288 GB HBM3e VRAM and 2300 TFLOPS FP32 handle massive datasets and trillion-parameter models without memory constraints. RTX 5000 Ada's 32 GB limits scale.
4600 TFLOPS FP8 on MI355X with 8000 GB/s bandwidth supports high-throughput serving of large LLMs. RTX 5000 Ada's 65.3 TFLOPS FP16 falls short for production scale.
MI355X 2300 TFLOPS FP16 enables efficient fine-tuning of models over 70B parameters. RTX 5000 Ada suits only smaller models due to 32 GB VRAM.
RTX 5000 Ada's 65.3 TFLOPS FP16 and $0.25/hr pricing optimize image generation workflows. MI355X's 750W TDP overpowers typical creative tasks.
MI355X 2300 TFLOPS FP32 and Infinity Fabric excel in simulations requiring high memory bandwidth of 8000 GB/s. RTX 5000 Ada lacks capacity for complex datasets.
Frequently Asked Questions
What is the VRAM difference between MI355X and RTX 5000 Ada?▾
MI355X provides 288 GB HBM3e VRAM, enabling massive model handling. RTX 5000 Ada offers 32 GB GDDR6, suitable for mid-range tasks. This ninefold gap affects batch sizes in AI training.
How do FP16 performance levels compare?▾
MI355X delivers 2300 TFLOPS FP16, vastly outpacing RTX 5000 Ada's 65.3 TFLOPS. The MI355X processes tensor operations over 35 times faster for deep learning. This impacts training speed directly.
What are the TDPs of these GPUs?▾
MI355X requires 750W TDP for its dense compute. RTX 5000 Ada uses 250W, easing power and cooling needs. Choose based on infrastructure capacity.
Is there cloud pricing for MI355X?▾
No live offers exist for MI355X currently. RTX 5000 Ada starts at $0.25/hr average $0.51/hr across five providers. Availability favors RTX for immediate use.
Which has higher memory bandwidth?▾
MI355X achieves 8000 GB/s with HBM3e, compared to RTX 5000 Ada's 576 GB/s GDDR6. This supports larger batches in inference without bottlenecks.
What architectures power these GPUs?▾
MI355X uses CDNA 4 from 2025 for data center optimization. RTX 5000 Ada employs Ada Lovelace from 2023 for professional versatility. CDNA 4 prioritizes raw AI compute.
Which is cheaper to rent, the MI355X or the RTX 5000 Ada?▾
Cloud rental prices for both the MI355X and RTX 5000 Ada 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 RTX 5000 Ada?▾
The MI355X has 288 GB of HBM3e memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find MI355X and RTX 5000 Ada 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 RTX 5000 Ada?▾
The MI355X uses the CDNA 4 architecture (2025) while the RTX 5000 Ada uses Ada Lovelace (2023). The MI355X delivers 35.2x the FP16 throughput and 13.9x the memory bandwidth of the RTX 5000 Ada.