Specifications Compared
| Spec | MI300X | RTX-5000-ADA |
|---|---|---|
| TDP | 750W | 250W |
| VRAM | 192 GB | 32 GB |
| Memory Type | HBM3 | GDDR6 |
| Architecture | CDNA 3 | Ada Lovelace |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric, PCIe 5.0 | |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 163 TFLOPS | 65.3 TFLOPS |
| FP64 Performance | 81.7 TFLOPS | |
| INT8 Performance | 2,614 TOPS | 1,044 TOPS |
| Memory Bandwidth | 5,300 GB/s | 576 GB/s |
Performance Analysis
The MI300X vastly outpaces the RTX 5000 Ada in compute performance: 1307 TFLOPS FP16 versus 65.3 TFLOPS enables 20 times faster tensor operations critical for AI training and inference. Its FP32 rate of 163 TFLOPS exceeds the RTX 5000 Ada's matched 65.3 TFLOPS, benefiting simulation and rendering tasks. The FP8 capability of 2614 TFLOPS on MI300X accelerates low-precision inference for large language models, reducing latency in deployment scenarios.
Memory specifications define workload scalability: 192 GB HBM3 on MI300X supports massive batch sizes for training billion-parameter models, while 32 GB GDDR6 on RTX 5000 Ada limits to smaller datasets. Bandwidth disparity is stark at 5300 GB/s versus 576 GB/s, allowing MI300X to handle data-intensive operations without bottlenecks, sustaining high throughput in multi-GPU setups via Infinity Fabric.
Power draw reflects deployment constraints: MI300X's 750W TDP suits data centers with robust cooling, whereas RTX 5000 Ada's 250W fits edge or workstation environments. These differences translate to real-world efficiency where MI300X excels in throughput per hour despite higher energy use.
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×) |
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 MI300X
Select the MI300X for large-scale AI training or inference requiring over 192 GB VRAM, such as processing models with billions of parameters. Its 5300 GB/s bandwidth and 1307 TFLOPS FP16 performance enable handling enormous batch sizes without memory swaps, ideal for research labs or enterprises on cloud platforms offering it from $0.50 per hour.
The GPU shines in FP8-heavy inference workloads at 2614 TFLOPS, outperforming RTX 5000 Ada by orders of magnitude for high-volume serving.
When to Choose the RTX 5000 Ada
Opt for the RTX 5000 Ada in cost-sensitive prototyping or workstation tasks where 32 GB VRAM suffices, available from $0.25 per hour. Its 250W TDP and PCIe form factor integrate easily into smaller clusters or local setups without extensive power infrastructure.
It suits graphics-intensive applications leveraging Ada Lovelace efficiency at 65.3 TFLOPS FP16 and FP32, balancing performance with an average cloud price of $0.51 per hour.
Use Cases
MI300X's 192 GB HBM3 VRAM and 1307 TFLOPS FP16 support training massive LLMs with large batch sizes. RTX 5000 Ada's 32 GB limits model scale.
The 2614 TFLOPS FP8 on MI300X accelerates high-throughput inference for deployed LLMs. Its 5300 GB/s bandwidth handles concurrent requests efficiently.
MI300X accommodates full model fine-tuning with 192 GB VRAM, avoiding gradient checkpointing. RTX 5000 Ada works for smaller models but constrains parameter counts.
RTX 5000 Ada's Ada Lovelace architecture optimizes image generation at 65.3 TFLOPS FP16 with lower 250W TDP. MI300X overkill for typical diffusion batch sizes.
MI300X delivers 163 TFLOPS FP32 for simulations, paired with 5300 GB/s bandwidth for large datasets. Its capacity exceeds RTX 5000 Ada's for complex HPC tasks.
Frequently Asked Questions
Which GPU has more VRAM: MI300X or RTX 5000 Ada?▾
The MI300X provides 192 GB HBM3 VRAM, six times the RTX 5000 Ada's 32 GB GDDR6. This enables MI300X to load larger models without offloading. Cloud users benefit from MI300X for memory-bound tasks.
How do cloud prices compare for MI300X and RTX 5000 Ada?▾
MI300X starts at $0.50 per hour with an average of $2.63 across 9 offers, while RTX 5000 Ada begins at $0.25 per hour averaging $0.51 over 5 offers. RTX 5000 Ada offers better value for light workloads. Check gpuperhour.com for live rates.
What is the FP16 performance difference?▾
MI300X achieves 1307 TFLOPS FP16, 20 times the RTX 5000 Ada's 65.3 TFLOPS. This gap accelerates AI training significantly on MI300X. Inference benefits similarly from the compute lead.
Which has higher memory bandwidth?▾
MI300X delivers 5300 GB/s, over nine times the RTX 5000 Ada's 576 GB/s. Higher bandwidth on MI300X supports larger batches in deep learning. It reduces data transfer bottlenecks in multi-GPU training.
Is MI300X or RTX 5000 Ada better for power efficiency?▾
RTX 5000 Ada consumes 250W TDP versus MI300X's 750W, making it more efficient for smaller deployments. MI300X prioritizes raw performance over power draw. Choose based on infrastructure cooling capacity.
Can RTX 5000 Ada handle large model training?▾
RTX 5000 Ada's 32 GB VRAM limits it to models under that threshold, unlike MI300X's 192 GB. Techniques like quantization help but reduce precision. MI300X suits unrestricted large-scale training.
Which is cheaper to rent, the MI300X or the RTX 5000 Ada?▾
Cloud rental prices for both the MI300X 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 MI300X have compared to the RTX 5000 Ada?▾
The MI300X has 192 GB of HBM3 memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find MI300X 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 MI300X and the RTX 5000 Ada?▾
The MI300X uses the CDNA 3 architecture (2023) while the RTX 5000 Ada uses Ada Lovelace (2023). The MI300X delivers 20.0x the FP16 throughput and 9.2x the memory bandwidth of the RTX 5000 Ada.