Specifications Compared
| Spec | MI300X | RTX-2060 |
|---|---|---|
| TDP | 750W | 160W |
| VRAM | 192 GB | 6-12 GB |
| Memory Type | HBM3 | GDDR6 |
| Architecture | CDNA 3 | Turing |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric, PCIe 5.0 | |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 6.5 TFLOPS |
| FP32 Performance | 163 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 81.7 TFLOPS | |
| INT8 Performance | 2,614 TOPS | |
| Memory Bandwidth | 5,300 GB/s | 336 GB/s |
Performance Analysis
The MI300X's FP16 performance of 1307 TFLOPS vastly exceeds the RTX 2060 Super's 7.2 TFLOPS, enabling faster AI model training where half-precision computations dominate. Its FP32 rate of 163 TFLOPS remains superior to the 7.2 TFLOPS on the RTX 2060 Super, supporting general-purpose simulations effectively. This FP16 to FP32 delta on the MI300X, over eight times higher in FP16, accelerates deep learning pipelines while the RTX 2060 Super's parity suits graphics rendering. Memory bandwidth defines practical limits: 5300 GB/s on the MI300X handles massive batch sizes for large language models, fitting models up to 192 GB VRAM without swapping, whereas 448 GB/s and 8 GB VRAM on the RTX 2060 Super restrict it to small batches or quantized inference. Power draw underscores efficiency gaps, with the MI300X at 750W for datacenter density versus 175W on the RTX 2060 Super for edge deployments. Overall, these specs translate to orders-of-magnitude throughput differences in AI versus playable frame rates in games.
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 large-scale AI training and inference, leveraging 192 GB HBM3 VRAM to load full models like 70B-parameter LLMs without partitioning. Its 1307 TFLOPS FP16 and 5300 GB/s bandwidth support high-batch scientific computing or multi-GPU clusters via Infinity Fabric and PCIe 5.0. Cloud users benefit from offers starting at $0.50 per hour for sustained high-throughput workloads.
When to Choose the RTX 2060 SUPER
The RTX 2060 Super fits gaming, video editing, or small-scale inference where 8 GB GDDR6 VRAM and 448 GB/s bandwidth suffice for 1080p resolutions or lightweight Stable Diffusion. Its 175W TDP enables desktop or low-power cloud instances without datacenter cooling. With no live cloud offers, it appeals for on-premises setups prioritizing affordability over scale.
Use Cases
The MI300X's 192 GB HBM3 VRAM and 1307 TFLOPS FP16 handle massive datasets and large models, enabling efficient training of billion-parameter LLMs. The RTX 2060 Super's 8 GB VRAM limits it to toy models.
MI300X supports high-throughput inference with 5300 GB/s bandwidth for large batch sizes on 192 GB VRAM. RTX 2060 Super restricts to small or quantized models due to 448 GB/s and 8 GB limits.
MI300X's 163 TFLOPS FP32 and vast VRAM accelerate fine-tuning of large models without memory constraints. RTX 2060 Super struggles with models exceeding 8 GB.
RTX 2060 Super's Turing architecture and 7.2 TFLOPS FP32 deliver smooth image generation at 1080p with 8 GB VRAM. MI300X is overprovisioned for consumer creative tasks.
MI300X's 5300 GB/s bandwidth and 750W TDP scale simulations across OAM form factors. RTX 2060 Super's PCIe limits multi-GPU scientific runs.
Frequently Asked Questions
What is the VRAM difference between MI300X and RTX 2060 Super?▾
The MI300X has 192 GB HBM3 VRAM, enabling large model hosting. The RTX 2060 Super provides 8 GB GDDR6, suitable for smaller workloads. This 24-fold gap affects batch sizes directly.
Which GPU has higher FP16 performance?▾
MI300X achieves 1307 TFLOPS FP16, over 180 times the RTX 2060 Super's 7.2 TFLOPS. This favors MI300X for AI acceleration. RTX 2060 Super suffices for basic tensor operations.
What are the cloud pricing details?▾
MI300X offers start at $0.50 per hour, averaging $2.63 per hour across nine providers. No live offers exist for RTX 2060 Super. Pricing reflects datacenter versus consumer focus.
How do power consumptions compare?▾
MI300X draws 750W TDP for high-density compute. RTX 2060 Super uses 175W, ideal for desktops. The difference impacts deployment costs and cooling needs.
Which is better for gaming?▾
RTX 2060 Super excels with Turing RT cores for ray tracing at 7.2 TFLOPS FP32. MI300X lacks gaming optimizations despite superior specs. It targets compute only.
What architectures do they use?▾
MI300X employs CDNA 3 from 2023 for AI. RTX 2060 Super uses Turing from 2019 for graphics. The four-year gap drives MI300X's spec advantages.
Which is cheaper to rent, the MI300X or the RTX 2060?▾
Cloud rental prices for both the MI300X and RTX 2060 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 2060?▾
The MI300X has 192 GB of HBM3 memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.
Can I find MI300X and RTX 2060 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 2060?▾
The MI300X uses the CDNA 3 architecture (2023) while the RTX 2060 uses Turing (2019). The MI300X delivers 201.1x the FP16 throughput and 15.8x the memory bandwidth of the RTX 2060.