RTX 2060 SUPER vs RTX 2070 SUPER

TuringvsTuringUpdated 35 days ago

The RTX 2070 Super emerges as the winner for most machine learning use cases due to its 9.1 TFLOPS performance, a 26 percent edge over the RTX 2060 Super's 7.2 TFLOPS. This boost accelerates training and inference, outweighing the higher 215 W TDP for compute-focused cloud rentals.

Specifications Compared

SpecRTX-2060RTX-2070
TDP160W175W
VRAM6-12 GB8 GB
CUDA Cores1,9202,304
Memory TypeGDDR6GDDR6
ArchitectureTuringTuring
Form FactorsPCIePCIe
InterconnectNVLink
Tensor Cores240288
FP16 Performance6.5 TFLOPS7.5 TFLOPS
FP32 Performance6.5 TFLOPS7.5 TFLOPS
Memory Bandwidth336 GB/s448 GB/s

Performance Analysis

The RTX 2070 Super's 9.1 TFLOPS FP16 and FP32 performance exceeds the RTX 2060 Super's 7.2 TFLOPS by 26 percent, translating to faster model training and inference in deep learning pipelines. For training large language models, this delta accelerates gradient computations and backpropagation, reducing epoch times proportionally in FP32-heavy workflows.

Memory bandwidth at 448 GB/s is identical, supporting comparable batch sizes in memory-bound tasks like Stable Diffusion generation or fine-tuning. Neither GPU faces bottlenecks in loading 8 GB models, but the RTX 2070 Super processes data quicker due to higher throughput.

The TDP difference of 175 W versus 215 W implies the RTX 2060 Super consumes less power for lighter inference, potentially lowering cloud costs in prolonged sessions. However, for compute-intensive scientific computing, the RTX 2070 Super's superior FLOPS yield better overall throughput despite increased energy use.

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When to Choose the RTX 2060 SUPER

The RTX 2060 Super suits budget-conscious deployments with 175 W TDP and 7.2 TFLOPS performance. It excels in inference tasks for models under 8 GB, where its 448 GB/s bandwidth handles standard batch sizes efficiently. Power-limited cloud instances favor this GPU for cost savings without sacrificing viability in lighter ML workflows.

When to Choose the RTX 2070 SUPER

Opt for the RTX 2070 Super in demanding training scenarios leveraging its 9.1 TFLOPS FP16 and FP32 rates. The 26 percent compute advantage speeds fine-tuning and scientific simulations, justifying the 215 W TDP. It outperforms in bandwidth-saturated tasks despite shared 448 GB/s specs.

Use Cases

LLM Training
RTX 2070 SUPER

The RTX 2070 Super's 9.1 TFLOPS FP16/FP32 outperforms the 7.2 TFLOPS of the RTX 2060 Super, reducing training times by 26 percent in compute-heavy phases.

LLM Inference
Either

Both GPUs share 8 GB VRAM and 448 GB/s bandwidth, supporting similar batch sizes for inference. Compute differences matter less in latency-optimized deployments.

Fine-tuning
RTX 2070 SUPER

Higher 9.1 TFLOPS on the RTX 2070 Super accelerates gradient updates during fine-tuning compared to 7.2 TFLOPS on the RTX 2060 Super.

Stable Diffusion
RTX 2070 SUPER

The RTX 2070 Super's superior 9.1 TFLOPS handles diffusion steps faster, improving generation throughput over the RTX 2060 Super's 7.2 TFLOPS.

Scientific Computing
RTX 2070 SUPER

Compute-intensive simulations benefit from the 26 percent higher FP32 performance of 9.1 TFLOPS on the RTX 2070 Super versus 7.2 TFLOPS.

Frequently Asked Questions

Which has more VRAM: RTX 2060 Super or RTX 2070 Super?

Both GPUs feature 8 GB GDDR6 VRAM. This capacity supports models up to that size without offloading, with identical 448 GB/s bandwidth for data access.

RTX 2060 Super vs 2070 Super: which is faster for AI training?

The RTX 2070 Super is faster with 9.1 TFLOPS FP16/FP32 versus 7.2 TFLOPS on the RTX 2060 Super. This yields about 26 percent quicker training iterations.

What is the power consumption difference?

The RTX 2060 Super has a 175 W TDP, lower than the RTX 2070 Super's 215 W. Lower TDP reduces operational costs in power-metered cloud environments.

Can RTX 2060 Super handle Stable Diffusion?

Yes, its 8 GB VRAM and 448 GB/s bandwidth support Stable Diffusion at standard resolutions. However, the RTX 2070 Super generates images 26 percent faster due to higher TFLOPS.

Are both GPUs from the same generation?

Both use Turing architecture from 2019. They share PCIe form factors, making them drop-in compatible for cloud GPU comparisons.

Which is better for inference batch sizes?

Batch sizes are similar on both due to matching 8 GB VRAM and 448 GB/s bandwidth. The RTX 2070 Super processes larger effective batches faster with 9.1 TFLOPS.

Which is cheaper to rent, the RTX 2060 or the RTX 2070?

Cloud rental prices for both the RTX 2060 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 RTX 2060 have compared to the RTX 2070?

The RTX 2060 has 6 to 12 GB of GDDR6 memory. The RTX 2070 has 8 GB of GDDR6 memory.

Can I find RTX 2060 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 RTX 2060 and the RTX 2070?

The RTX 2060 uses the Turing architecture (2019) while the RTX 2070 uses Turing (2018). The RTX 2070 delivers 1.2x the FP16 throughput and 1.3x the memory bandwidth of the RTX 2060.

RTX 2060 SUPER vs RTX 2070 SUPER: 12GB vs 8GB | GPUPerHour