Specifications Compared
| Spec | MI250X | RTX-2060 |
|---|---|---|
| TDP | 560W | 160W |
| VRAM | 128 GB | 6-12 GB |
| Memory Type | HBM2e | GDDR6 |
| Architecture | CDNA 2 | Turing |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric | |
| FP16 Performance | 383 TFLOPS | 6.5 TFLOPS |
| FP32 Performance | 383 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 48 TFLOPS | |
| Memory Bandwidth | 3,277 GB/s | 336 GB/s |
Performance Analysis
Raw compute power differs dramatically: the MI250X achieves 383 TFLOPS in FP16 and FP32, compared to the RTX 2060 SUPER's 6.5 TFLOPS, enabling up to 59 times faster matrix operations critical for AI training and inference. Equal FP16 and FP32 rates on the MI250X optimize balanced workloads, while the RTX 2060 SUPER suits graphics where tensor cores boost specific tasks.
Memory specs dictate real-world limits: 128 GB HBM2e at 3277 GB/s on the MI250X handles enormous batch sizes in model training, preventing out-of-memory errors for large LLMs, unlike the RTX 2060 SUPER's 6 to 12 GB GDDR6 at 336 GB/s, which caps batches at small scales. Higher bandwidth reduces data starvation in memory-bound inference, favoring the MI250X for throughput.
Power draw underscores deployment gaps: the MI250X's 560W TDP suits rack-scale servers, while the RTX 2060 SUPER's 160W fits desktops, impacting cooling and cost in edge computing.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
MI250X
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.28/GPU/hr $5.12/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.44/GPU/hr $5.76/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.52/GPU/hr $6.08/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.60/GPU/hr $6.40/hr total (4×) |
When to Choose the MI250X
Choose the AMD Instinct MI250X for large-scale AI training or scientific simulations requiring 128 GB VRAM: its 3277 GB/s bandwidth supports massive datasets without swapping. Cloud users benefit from $1.28 per hour pricing for high-utilization jobs like LLM fine-tuning, where 383 TFLOPS accelerates convergence.
Datacenter interconnects like Infinity Fabric enable multi-GPU scaling, ideal for clusters processing petabyte-scale data.
When to Choose the RTX 2060 SUPER
The NVIDIA GeForce RTX 2060 SUPER fits consumer desktops for gaming or light creative work: its 160W TDP and PCIe form factor integrate easily into personal rigs without datacenter infrastructure. For hobbyist inference on models under 6 GB, 6.5 TFLOPS suffices at zero cloud rental cost.
Absence of live cloud offers makes it preferable for on-premise setups avoiding hourly fees.
Use Cases
MI250X's 128 GB HBM2e VRAM and 383 TFLOPS FP16 handle billion-parameter models with large batches. RTX 2060 SUPER's 6-12 GB limits it to tiny models.
3277 GB/s bandwidth on MI250X enables high-throughput serving of large models. RTX 2060 SUPER's 336 GB/s bottlenecks concurrent requests.
MI250X supports full fine-tuning of models needing 128 GB VRAM at 383 TFLOPS speed. RTX 2060 SUPER restricts to parameter-efficient methods.
RTX 2060 SUPER runs standard Stable Diffusion with 6-12 GB VRAM for gaming rigs. MI250X excels in high-res batch generation but overkill for singles.
MI250X's 383 TFLOPS FP32 and Infinity Fabric suit HPC simulations. RTX 2060 SUPER's 6.5 TFLOPS limits complex fluid dynamics or genomics.
Frequently Asked Questions
Which GPU has more VRAM, MI250X or RTX 2060 SUPER?▾
The MI250X offers 128 GB HBM2e VRAM. The RTX 2060 SUPER provides 6 to 12 GB GDDR6, making MI250X superior for large models.
What is the memory bandwidth difference?▾
MI250X delivers 3277 GB/s with HBM2e. RTX 2060 SUPER achieves 336 GB/s on GDDR6, a nearly 10-fold gap impacting data-heavy tasks.
How do FP32 performances compare?▾
MI250X reaches 383 TFLOPS FP32. RTX 2060 SUPER hits 6.5 TFLOPS, so MI250X computes 59 times faster for simulations.
What are the cloud prices for these GPUs?▾
MI250X starts at $1.28 per hour, averaging $1.46 across four offers. No live cloud offers exist for RTX 2060 SUPER.
Which has higher power consumption?▾
MI250X draws 560W TDP for datacenter use. RTX 2060 SUPER uses 160W, suiting low-power desktops.
Can RTX 2060 SUPER handle AI training?▾
RTX 2060 SUPER manages small models with 6-12 GB VRAM. It cannot train large LLMs due to limited 6.5 TFLOPS and bandwidth.
Which is cheaper to rent, the MI250X or the RTX 2060?▾
Cloud rental prices for both the MI250X 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 MI250X have compared to the RTX 2060?▾
The MI250X has 128 GB of HBM2e memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.
Can I find MI250X 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 MI250X and the RTX 2060?▾
The MI250X uses the CDNA 2 architecture (2021) while the RTX 2060 uses Turing (2019). The MI250X delivers 58.9x the FP16 throughput and 9.8x the memory bandwidth of the RTX 2060.