Specifications Compared
| Spec | MI300X | RTX-5080 |
|---|---|---|
| TDP | 750W | 360W |
| VRAM | 192 GB | 16 GB |
| Memory Type | HBM3 | GDDR7 |
| Architecture | CDNA 3 | Blackwell |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric, PCIe 5.0 | |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 163 TFLOPS | 56.3 TFLOPS |
| FP64 Performance | 81.7 TFLOPS | |
| INT8 Performance | 2,614 TOPS | 900 TOPS |
| Memory Bandwidth | 5,300 GB/s | 960 GB/s |
Performance Analysis
Memory capacity defines workload feasibility: the MI300X's 192 GB HBM3 supports models exceeding 16 GB GDDR7 on the RTX 5080, enabling larger batch sizes in training without splitting across GPUs. Bandwidth at 5300 GB/s on MI300X versus 960 GB/s on RTX 5080 accelerates data movement, reducing bottlenecks in memory-intensive operations like transformer processing. FP16 performance shows stark divergence, with MI300X at 1307 TFLOPS dwarfing RTX 5080's 56.3 TFLOPS: this 23x gap favors MI300X for training where half-precision dominates, speeding iterations on massive datasets. Inference benefits from MI300X's FP8 at 2614 TFLOPS, absent on RTX 5080, for quantized models. FP32 parity tilts toward MI300X's 163 TFLOPS over 56.3 TFLOPS in simulations requiring full precision. Power draw of 750W on MI300X demands robust cooling, unlike 360W on RTX 5080, impacting deployment density.
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 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
When to Choose the MI300X
The MI300X suits large-scale AI training and inference where VRAM exceeds 16 GB, such as full-parameter fine-tuning of models like Llama 70B. Its 5300 GB/s bandwidth and 1307 TFLOPS FP16 enable high-throughput batches, ideal for research clusters or enterprise ML pipelines. Cloud users prioritize it when scaling justifies $2.63/hr average over smaller alternatives.
When to Choose the RTX 5080
The RTX 5080 fits cost-sensitive prototyping, gaming, or inference on models under 16 GB VRAM, leveraging 56.3 TFLOPS FP16 at $0.38/hr average. Its 360W TDP and PCIe form factor simplify single-node setups for developers testing Stable Diffusion or lightweight LLMs. Bandwidth of 960 GB/s suffices for consumer-scale tasks without datacenter overhead.
Use Cases
MI300X's 192 GB HBM3 and 1307 TFLOPS FP16 handle large models and batches infeasible on RTX 5080's 16 GB VRAM.
The 2614 TFLOPS FP8 and 5300 GB/s bandwidth on MI300X accelerate high-volume quantized inference beyond RTX 5080's capabilities.
MI300X supports full-model fine-tuning with 192 GB VRAM, while RTX 5080 limits to parameter-efficient methods under 16 GB.
RTX 5080's 56.3 TFLOPS FP16 and lower $0.38/hr cost optimize image generation workflows fitting within 16 GB GDDR7.
MI300X's 163 TFLOPS FP32 and Infinity Fabric interconnect excel in simulations requiring high precision and multi-GPU scaling.
Frequently Asked Questions
Which GPU has more VRAM?▾
The MI300X provides 192 GB HBM3, surpassing RTX 5080's 16 GB GDDR7 by 12 times. This enables larger AI models on MI300X. Bandwidth follows suit at 5300 GB/s versus 960 GB/s.
What is the FP16 performance difference?▾
MI300X delivers 1307 TFLOPS FP16, 23 times higher than RTX 5080's 56.3 TFLOPS. This gap accelerates AI training significantly. FP8 on MI300X reaches 2614 TFLOPS for inference.
How do cloud prices compare?▾
RTX 5080 starts at $0.25/hr with $0.38/hr average across 4 offers, cheaper than MI300X's $0.50/hr start and $2.63/hr average across 9 offers. Cost favors RTX for light use. Scale justifies MI300X pricing.
What are the power requirements?▾
MI300X consumes 750W TDP in OAM form factor, demanding datacenter power. RTX 5080 uses 360W in PCIe, suiting varied setups. This affects cooling and density.
Which is better for LLM inference?▾
MI300X excels with 192 GB VRAM and 2614 TFLOPS FP8 for large-scale serving. RTX 5080 handles smaller models at lower cost. Batch size limits RTX to 16 GB contexts.
What architectures do they use?▾
MI300X employs CDNA 3 from 2023 with Infinity Fabric. RTX 5080 uses Blackwell from 2025. Interconnects differ: PCIe 5.0 on MI300X, PCIe on RTX 5080.
Which is cheaper to rent, the MI300X or the RTX 5080?▾
Cloud rental prices for both the MI300X and RTX 5080 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 5080?▾
The MI300X has 192 GB of HBM3 memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find MI300X and RTX 5080 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 5080?▾
The MI300X uses the CDNA 3 architecture (2023) while the RTX 5080 uses Blackwell (2025). The MI300X delivers 23.2x the FP16 throughput and 5.5x the memory bandwidth of the RTX 5080.