Specifications Compared
| Spec | MI300X | QUADRO-RTX-8000 |
|---|---|---|
| TDP | 750W | 260W |
| VRAM | 192 GB | 48 GB |
| Memory Type | HBM3 | GDDR6 |
| Architecture | CDNA 3 | Turing |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric, PCIe 5.0 | NVLink |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 163 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 81.7 TFLOPS | |
| INT8 Performance | 2,614 TOPS | |
| Memory Bandwidth | 5,300 GB/s | 672 GB/s |
Performance Analysis
Memory capacity defines a core disparity: the MI300X's 192 GB HBM3 supports batch sizes for models exceeding hundreds of billions of parameters, while the RTX 8000's 48 GB GDDR6 limits it to smaller datasets. Bandwidth amplifies this: 5300 GB/s on MI300X enables rapid data movement for training loops, reducing bottlenecks in inference at scale, compared to 672 GB/s on RTX 8000 which suits moderate workloads.
Compute throughput reveals AI specialization: MI300X FP16 at 1307 TFLOPS accelerates mixed-precision training, where FP32 at 163 TFLOPS handles simulations; RTX 8000 matches 16.3 TFLOPS in both, adequate for legacy FP32-dominant tasks but insufficient for modern deep learning. FP8 on MI300X reaches 2614 TFLOPS, optimizing low-precision inference absent on RTX 8000.
Power draw impacts deployment: MI300X's 750W TDP demands robust cooling for datacenters, versus RTX 8000's efficient 260W for workstations, influencing total cost of ownership in edge computing.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
MI300X
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | AMD Instinct MI300X 192GB VRAM | 192GB | 24 vCPU 256GB RAM | 🌍global | $1.99/GPU/hr | |||
 Hot Aisle | AMD Instinct MI300X 192GB VRAM | 192GB | 8 vCPU 224GB RAM 12288GB Storage | Michigan | $1.99/GPU/hr | Available | ||
 Cirrascale | 8×AMD Instinct MI300X 192GB VRAM | 192GB | 192 vCPU 2355GB RAM 44538GB Storage | United States | $3.08/GPU/hr $24.64/hr total (8×) | |||
 Crusoe | AMD Instinct MI300X 192GB VRAM | 192GB | 0 vCPU 0GB RAM | United States | $3.45/GPU/hr | |||
Cirrascale | 8×AMD Instinct MI300X 192GB VRAM | 192GB | 192 vCPU 2355GB RAM 44538GB Storage | United States | $3.47/GPU/hr $27.76/hr total (8×) |
When to Choose the MI300X
The MI300X excels in datacenter-scale AI training and inference: its 192 GB VRAM and 5300 GB/s bandwidth handle large language models with batch sizes infeasible on 48 GB alternatives. Cloud availability from $0.50 per hour suits bursty workloads without upfront hardware costs.
Scientific simulations benefit from 1307 TFLOPS FP16 and Infinity Fabric interconnects, enabling distributed computing across PCIe 5.0 nodes.
When to Choose the Quadro RTX 8000
The RTX 8000 fits legacy workstation upgrades: its PCIe form factor and 260W TDP integrate easily into existing professional setups for CAD or rendering. NVLink supports multi-GPU visualization where 16.3 TFLOPS FP32 suffices for real-time tasks.
Power-sensitive environments or used hardware budgets favor it, as no cloud offers exist, avoiding MI300X's 750W demands.
Use Cases
MI300X's 1307 TFLOPS FP16 and 192 GB VRAM support massive batch sizes for training billion-parameter models. RTX 8000's 16.3 TFLOPS and 48 GB limit it to small-scale experiments.
2614 TFLOPS FP8 and 5300 GB/s bandwidth on MI300X deliver high-throughput serving. RTX 8000 cannot compete with 672 GB/s for production-scale queries.
163 TFLOPS FP32 and HBM3 enable efficient parameter updates on large models. RTX 8000's matching 16.3 TFLOPS FP32 restricts dataset sizes.
MI300X accelerates generation with 1307 TFLOPS FP16 for high-res outputs. RTX 8000 handles standard resolutions at 16.3 TFLOPS in workstations.
Infinity Fabric and 5300 GB/s bandwidth optimize simulations. RTX 8000's NVLink suits smaller clusters but lacks capacity.
Frequently Asked Questions
What is the VRAM difference between MI300X and Quadro RTX 8000?▾
MI300X provides 192 GB HBM3, enabling large model handling. Quadro RTX 8000 offers 48 GB GDDR6, suitable for moderate datasets. This quadruples capacity for MI300X.
How do FP16 performance levels compare?▾
MI300X achieves 1307 TFLOPS in FP16 for AI acceleration. Quadro RTX 8000 reaches 16.3 TFLOPS, about 80 times lower. MI300X dominates training tasks.
What are the cloud pricing options?▾
MI300X rentals start at $0.50 per hour, averaging $2.63 across nine providers. Quadro RTX 8000 has no live cloud offers. On-premises purchase applies for RTX 8000.
Which has higher memory bandwidth?▾
MI300X delivers 5300 GB/s with HBM3. Quadro RTX 8000 provides 672 GB/s via GDDR6. Nearly eightfold advantage aids MI300X in data-intensive jobs.
Compare power consumption and form factors?▾
MI300X uses 750W in OAM for datacenters. Quadro RTX 8000 draws 260W in PCIe for workstations. RTX 8000 suits lower-power setups.
Is MI300X better for LLM workloads?▾
Yes, with 2614 TFLOPS FP8 and 192 GB VRAM for inference. RTX 8000's 16.3 TFLOPS limits it to prototypes. MI300X scales production.
Which is cheaper to rent, the MI300X or the Quadro RTX 8000?▾
Cloud rental prices for both the MI300X 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 MI300X have compared to the Quadro RTX 8000?▾
The MI300X has 192 GB of HBM3 memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.
Can I find MI300X 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 MI300X and the Quadro RTX 8000?▾
The MI300X uses the CDNA 3 architecture (2023) while the Quadro RTX 8000 uses Turing (2018). The MI300X delivers 80.2x the FP16 throughput and 7.9x the memory bandwidth of the Quadro RTX 8000.