Specifications Compared
| Spec | MI325X | RTX-2070 |
|---|---|---|
| TDP | 750W | 175W |
| VRAM | 256 GB | 8 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | CDNA 3 | Turing |
| Form Factors | OAM | PCIe |
| Interconnect | Infinity Fabric | NVLink |
| FP8 Performance | 2,614 TFLOPS | |
| FP16 Performance | 1,307 TFLOPS | 7.5 TFLOPS |
| FP32 Performance | 1307 TFLOPS | 7.5 TFLOPS |
| FP64 Performance | 40.9 TFLOPS | |
| INT8 Performance | 2,614 TOPS | |
| Memory Bandwidth | 6,000 GB/s | 448 GB/s |
Performance Analysis
Compute performance reveals a chasm: the MI325X achieves 1307 TFLOPS in FP16 and FP32, dwarfing the RTX 2070 SUPER's 9 TFLOPS in both, which translates to over 145 times faster matrix operations critical for deep learning. This delta means the MI325X accelerates neural network training cycles from days to hours for large models, whereas the RTX 2070 SUPER handles only modest workloads. Equal FP16 and FP32 rates on each GPU indicate balanced scalar and half-precision compute, but the MI325X's FP8 at 2614 TFLOPS further boosts inference efficiency. Memory bandwidth of 6000 GB/s on the MI325X versus 448 GB/s on the RTX 2070 SUPER supports batch sizes up to 13 times larger, minimizing data transfer bottlenecks and enabling stable training of billion-parameter models without out-of-memory errors. In real-world terms, the RTX 2070 SUPER suffices for prototyping, but scales poorly beyond 1-2 GB models.
Live Cloud Pricing
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When to Choose the MI325X
Select the MI325X for data center deployments involving large-scale AI training or inference, where 256 GB HBM3e VRAM handles models exceeding 100 billion parameters. Its 6000 GB/s bandwidth and 1307 TFLOPS FP16 ensure high throughput in HPC simulations or multi-GPU clusters via Infinity Fabric. Professional environments prioritizing raw performance over power efficiency favor this GPU.
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER excels in consumer desktops for gaming, lightweight inference, or development prototyping with models under 8 GB VRAM. Its 215W TDP and PCIe form factor integrate easily into standard PCs without specialized cooling. Budget-conscious users or those needing NVLink for small SLI setups choose it over datacenter hardware.
Use Cases
The MI325X's 256 GB VRAM and 1307 TFLOPS FP16 support training LLMs with hundreds of billions of parameters, far beyond the RTX 2070 SUPER's 8 GB limit. Its 6000 GB/s bandwidth sustains large batch sizes for efficient convergence.
MI325X FP8 performance at 2614 TFLOPS and high bandwidth enable low-latency serving of massive models. The RTX 2070 SUPER's 9 TFLOPS restricts it to small-scale inference.
With 1307 TFLOPS FP32 and ample VRAM, the MI325X fine-tunes large models rapidly. RTX 2070 SUPER handles only tiny datasets due to 8 GB constraint.
MI325X's memory capacity supports high-resolution generations and batch processing at 6000 GB/s speeds. RTX 2070 SUPER manages basic image synthesis but slows on complex prompts.
The MI325X's 1307 TFLOPS FP32 and OAM form factor excel in simulations requiring vast memory. RTX 2070 SUPER suits entry-level tasks but lacks scale.
Frequently Asked Questions
What is the VRAM difference between MI325X and RTX 2070 SUPER?▾
The MI325X offers 256 GB HBM3e VRAM, while the RTX 2070 SUPER has 8 GB GDDR6, a 32 times increase. This allows the MI325X to process datasets and models infeasible on the consumer card. Bandwidth follows suit at 6000 GB/s versus 448 GB/s.
How do FP16 performance levels compare?▾
MI325X delivers 1307 TFLOPS FP16, over 145 times the RTX 2070 SUPER's 9 TFLOPS. This gap accelerates AI training and inference dramatically on the MI325X. FP32 matches at 1307 TFLOPS versus 9 TFLOPS.
What are the power requirements?▾
The MI325X has a 750W TDP suited for rack servers, compared to the RTX 2070 SUPER's 215W for desktops. Lower power on the SUPER enables easy integration in consumer builds. Efficiency per watt favors the MI325X for high-end tasks.
Which is better for AI training?▾
MI325X dominates with 256 GB VRAM and 6000 GB/s bandwidth for large LLMs. RTX 2070 SUPER limits training to small models under 8 GB. Datacenter interconnects like Infinity Fabric enhance MI325X scaling.
Can RTX 2070 SUPER handle machine learning?▾
Yes, the RTX 2070 SUPER manages prototyping and inference at 9 TFLOPS FP16 with 8 GB VRAM. It falls short for production-scale work versus MI325X's 1307 TFLOPS. Gaming remains its strength.
What architectures do they use?▾
MI325X employs CDNA 3 from 2024 for AI optimization, while RTX 2070 SUPER uses Turing from 2018 for gaming and general compute. This six-year gap underscores MI325X's advancements in memory and flops.
Which is cheaper to rent, the MI325X or the RTX 2070?▾
Cloud rental prices for both the MI325X and RTX 2070 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 MI325X have compared to the RTX 2070?▾
The MI325X has 256 GB of HBM3e memory. The RTX 2070 has 8 GB of GDDR6 memory.
Can I find MI325X and RTX 2070 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 MI325X and the RTX 2070?▾
The MI325X uses the CDNA 3 architecture (2024) while the RTX 2070 uses Turing (2018). The MI325X delivers 174.3x the FP16 throughput and 13.4x the memory bandwidth of the RTX 2070.