Specifications Compared
| Spec | MI355X | QUADRO-RTX-8000 |
|---|---|---|
| TDP | 750W | 260W |
| VRAM | 288 GB | 48 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | CDNA 4 | Turing |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric | NVLink |
| FP8 Performance | 4,600 TFLOPS | |
| FP16 Performance | 2,300 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 2300 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 72 TFLOPS | |
| INT8 Performance | 4,600 TOPS | |
| Memory Bandwidth | 8,000 GB/s | 672 GB/s |
Performance Analysis
Compute throughput defines the core performance gap: the MI355X achieves 2300 TFLOPS in FP16 and FP32, enabling rapid training of massive neural networks, while the RTX 8000 manages only 16.3 TFLOPS in both, suitable merely for smaller-scale tasks from 2018. This delta means training times on the MI355X could shrink by over 140 times for FP16-heavy deep learning, assuming linear scaling. Inference benefits similarly, with the MI355X's additional 4600 TFLOPS in FP8 accelerating low-precision deployments absent on the RTX 8000.
Memory capacity and speed transform real-world usability: 288 GB HBM3e on the MI355X supports enormous batch sizes for LLMs exceeding 100 billion parameters, whereas 48 GB GDDR6 on the RTX 8000 limits models to under 20 billion without heavy optimization. Bandwidth at 8000 GB/s versus 672 GB/s reduces bottlenecks in data loading, allowing the MI355X to sustain peak FLOPS during gradient computations or inference serving.
Power draw reflects efficiency trade-offs: the MI355X's 750W TDP demands robust cooling in racks, yet yields density for cloud providers, contrasting the RTX 8000's 260W for power-sensitive workstations. Overall, these specs render the MI355X dominant in AI pipelines, while the RTX 8000 suits legacy visualization.
Live Cloud Pricing
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When to Choose the MI355X
The MI355X excels in hyperscale AI training and inference where 288 GB HBM3e VRAM handles models too large for competitors: think trillion-parameter LLMs or genomic simulations requiring 2300 TFLOPS FP16. Its 8000 GB/s bandwidth ensures fluid large-batch processing in CDNA 4-optimized frameworks like ROCm.
Datacenter deployments favor the OAM form factor and Infinity Fabric for clustered scaling, ideal for cloud providers eyeing 2025-era efficiency despite 750W TDP.
When to Choose the Quadro RTX 8000
The Quadro RTX 8000 fits legacy workstation environments with its PCIe form factor and 260W TDP, consuming far less power than the MI355X's 750W. It suffices for CAD rendering or moderate ML prototyping using 48 GB GDDR6 and 16.3 TFLOPS FP32 on Turing drivers.
NVLink interconnects enable multi-GPU setups in pre-2020 software stacks where AMD compatibility lags, preserving investments in NVIDIA CUDA ecosystems.
Use Cases
The MI355X's 2300 TFLOPS FP16 and 288 GB HBM3e VRAM support massive batch sizes for trillion-parameter models. The RTX 8000's 16.3 TFLOPS and 48 GB limit it to small-scale training.
FP8 performance at 4600 TFLOPS on the MI355X accelerates high-throughput serving with 8000 GB/s bandwidth. The RTX 8000 lacks FP8 and bottlenecks at 672 GB/s.
288 GB VRAM on the MI355X enables full-model fine-tuning without sharding, backed by 2300 TFLOPS FP32. RTX 8000's 48 GB requires parameter-efficient methods.
MI355X handles high-resolution generations at scale with 2300 TFLOPS FP16 and vast VRAM. RTX 8000 manages basic diffusion but slows on large latents.
CDNA 4 architecture and 2300 TFLOPS FP32 on MI355X power complex simulations like climate modeling. RTX 8000's Turing limits precision-heavy HPC tasks.
Frequently Asked Questions
What is the VRAM difference between MI355X and Quadro RTX 8000?▾
The MI355X provides 288 GB HBM3e, six times the Quadro RTX 8000's 48 GB GDDR6. This allows the MI355X to load enormous AI models without offloading to host RAM.
How do FP16 performance figures compare?▾
MI355X delivers 2300 TFLOPS FP16, over 141 times the RTX 8000's 16.3 TFLOPS. Such disparity accelerates deep learning training dramatically on the newer GPU.
Which has higher memory bandwidth?▾
MI355X bandwidth reaches 8000 GB/s, nearly 12 times the RTX 8000's 672 GB/s. Higher bandwidth minimizes data stalls in large-batch inference.
What are the TDP ratings?▾
MI355X TDP is 750W for datacenter density, versus RTX 8000's 260W suited to workstations. The MI355X prioritizes peak performance over power efficiency.
Can Quadro RTX 8000 handle modern LLMs?▾
RTX 8000's 48 GB VRAM and 16.3 TFLOPS FP16 restrict it to models under 20B parameters with small batches. MI355X's 288 GB supports far larger LLMs seamlessly.
What architectures do they use?▾
MI355X employs CDNA 4 from 2025 for AI/HPC, while RTX 8000 uses Turing from 2018 for professional graphics. CDNA 4 includes FP8 at 4600 TFLOPS absent on Turing.
Which is cheaper to rent, the MI355X or the Quadro RTX 8000?▾
Cloud rental prices for both the MI355X and Quadro RTX 8000 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 Quadro RTX 8000?▾
The MI355X has 288 GB of HBM3e memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.
Can I find MI355X and Quadro RTX 8000 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 Quadro RTX 8000?▾
The MI355X uses the CDNA 4 architecture (2025) while the Quadro RTX 8000 uses Turing (2018). The MI355X delivers 141.1x the FP16 throughput and 11.9x the memory bandwidth of the Quadro RTX 8000.