Specifications Compared
| Spec | RTX-2060 | TITAN-V |
|---|---|---|
| TDP | 160W | 250W |
| VRAM | 6-12 GB | 12 GB |
| CUDA Cores | 1,920 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Turing | Volta |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 240 | 640 |
| FP16 Performance | 6.5 TFLOPS | 13.8 TFLOPS |
| FP32 Performance | 6.5 TFLOPS | 13.8 TFLOPS |
| Memory Bandwidth | 336 GB/s | 653 GB/s |
Performance Analysis
The TITAN V outperforms the RTX 2060 SUPER in raw compute with 13.8 TFLOPS FP16 and FP32 compared to 7.2 TFLOPS, translating to approximately 91 percent higher throughput in shader-limited training or inference tasks. This delta accelerates matrix multiplications in neural networks, reducing epoch times for models under 8 GB. For tensor core-heavy workloads, Volta's design provides consistent gains despite Turing's optimizations.
Memory specifications favor the TITAN V decisively: 12 GB HBM2 versus 8 GB GDDR6 enables larger models or batch sizes without swapping, while 653 GB/s bandwidth versus 448 GB/s minimizes data transfer bottlenecks during training. In inference, higher bandwidth supports bigger batches at lower latency, vital for real-time serving. The RTX 2060 SUPER's 175W TDP versus 250W allows denser deployments but limits sustained peak performance under thermal constraints.
Overall, these differences position the TITAN V for demanding AI pipelines, where compute and memory scale directly impact scalability, while the RTX 2060 SUPER suits lighter inference or fine-tuning with modest resource needs.
Live Cloud Pricing
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When to Choose the RTX 2060 SUPER
The RTX 2060 SUPER excels in power-constrained environments, drawing only 175W TDP compared to 250W for the TITAN V, enabling more instances per server rack. It suits entry-level machine learning tasks like fine-tuning small models under 8 GB VRAM or Stable Diffusion inference, where 7.2 TFLOPS FP32 suffices without memory bandwidth limitations at 448 GB/s. Users prioritizing efficiency over peak performance find value here.
When to Choose the TITAN V
Choose the TITAN V for memory-intensive workloads requiring 12 GB HBM2 VRAM and 653 GB/s bandwidth, such as training medium-sized LLMs or scientific simulations with large datasets. Its 13.8 TFLOPS FP16 and FP32 deliver faster iterations than the RTX 2060 SUPER's 7.2 TFLOPS, ideal when batch sizes exceed 8 GB limits.
Use Cases
The TITAN V's 12 GB HBM2 VRAM and 13.8 TFLOPS FP16 support larger models and batches compared to the RTX 2060 SUPER's 8 GB GDDR6 limit. Higher 653 GB/s bandwidth reduces data bottlenecks during training.
TITAN V handles bigger inference batches with 12 GB VRAM and 653 GB/s bandwidth, achieving lower latency than RTX 2060 SUPER's 8 GB and 448 GB/s. Its 13.8 TFLOPS FP32 ensures faster token generation.
RTX 2060 SUPER suffices for small models under 8 GB with 7.2 TFLOPS and 175W TDP efficiency. TITAN V accelerates larger fine-tuning via 12 GB VRAM and 13.8 TFLOPS.
RTX 2060 SUPER meets image generation needs with 8 GB VRAM and Turing tensor cores at 7.2 TFLOPS FP16. Lower 175W TDP fits consumer or edge deployments better than TITAN V's 250W.
TITAN V's 653 GB/s bandwidth and 12 GB HBM2 excel in simulations with high data throughput. 13.8 TFLOPS FP32 outperforms RTX 2060 SUPER's 7.2 TFLOPS for complex computations.
Frequently Asked Questions
Which GPU has more VRAM, RTX 2060 SUPER or TITAN V?▾
The TITAN V has 12 GB HBM2 VRAM, exceeding the RTX 2060 SUPER's 8 GB GDDR6. This allows the TITAN V to load larger models without out-of-memory errors. Bandwidth also favors TITAN V at 653 GB/s over 448 GB/s.
What is the FP32 performance difference?▾
TITAN V delivers 13.8 TFLOPS FP32, 91 percent higher than RTX 2060 SUPER's 7.2 TFLOPS. This impacts training speed in FP32-dominant tasks. FP16 matches this gap at 13.8 versus 7.2 TFLOPS.
Which has higher power consumption?▾
TITAN V requires 250W TDP, higher than RTX 2060 SUPER's 175W. This affects cloud costs and cooling needs. RTX 2060 SUPER enables more efficient multi-GPU setups.
Is TITAN V better for machine learning?▾
Yes, TITAN V suits most ML due to 12 GB VRAM, 653 GB/s bandwidth, and 13.8 TFLOPS compute. RTX 2060 SUPER works for lighter tasks under 8 GB models. Architecture age matters less than specs here.
What architectures do they use?▾
RTX 2060 SUPER uses Turing from 2019 with RT and tensor cores. TITAN V employs Volta from 2017, pioneering deep learning acceleration. Both support PCIe form factors.
Which is newer?▾
RTX 2060 SUPER released in 2019 under Turing, postdating TITAN V's 2017 Volta launch. Newer architecture brings efficiency gains despite lower peak specs. No live rental offers exist for either.
Which is cheaper to rent, the RTX 2060 or the TITAN V?▾
Cloud rental prices for both the RTX 2060 and TITAN V 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 TITAN V?▾
The RTX 2060 has 6 to 12 GB of GDDR6 memory. The TITAN V has 12 GB of HBM2 memory.
Can I find RTX 2060 and TITAN V 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 TITAN V?▾
The RTX 2060 uses the Turing architecture (2019) while the TITAN V uses Volta (2017). The TITAN V delivers 2.1x the FP16 throughput and 1.9x the memory bandwidth of the RTX 2060.