Quadro RTX 8000 vs RTX 2060

TuringvsTuringUpdated 35 days ago

The Quadro RTX 8000 emerges as the superior choice for most machine learning workloads on gpuperhour.com: its 48 GB VRAM and 16.3 TFLOPS handle large-scale training and inference infeasible on the RTX 2060's 6-12 GB and 6.5 TFLOPS. Despite lacking current pricing, its specs dominate professional use cases over the budget RTX 2060.

Specifications Compared

SpecQUADRO-RTX-8000RTX-2060
TDP260W160W
VRAM48 GB6-12 GB
CUDA Cores4,6081,920
Memory TypeGDDR6GDDR6
ArchitectureTuringTuring
Form FactorsPCIePCIe
InterconnectNVLink
Tensor Cores576240
FP16 Performance16.3 TFLOPS6.5 TFLOPS
FP32 Performance16.3 TFLOPS6.5 TFLOPS
Memory Bandwidth672 GB/s336 GB/s

Performance Analysis

The Quadro RTX 8000's 16.3 TFLOPS FP16 and FP32 performance doubles the RTX 2060's 6.5 TFLOPS in both precisions, enabling roughly twice the throughput for deep learning training and inference tasks. This compute advantage accelerates matrix multiplications central to neural networks, reducing epoch times in proportion to the TFLOPS delta.

Memory capacity defines the core distinction: 48 GB VRAM on the Quadro RTX 8000 supports batch sizes and model parameters infeasible on the RTX 2060's 6-12 GB, such as large language models exceeding 10 billion parameters. Bandwidth at 672 GB/s versus 336 GB/s further amplifies this, minimizing data transfer bottlenecks during training where high batch sizes demand rapid memory access.

Power efficiency tilts toward the RTX 2060 at 160W TDP versus 260W, yielding better perf-per-watt for light workloads. However, for memory-bound inference on sizable models, the Quadro RTX 8000 sustains higher utilization without swapping to system RAM.

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When to Choose the Quadro RTX 8000

The Quadro RTX 8000 suits enterprise machine learning pipelines requiring 48 GB VRAM, such as training transformer models with billions of parameters. Its 672 GB/s bandwidth and NVLink support excel in multi-GPU scientific simulations or large-scale rendering where the RTX 2060's 6-12 GB limits scalability.

Professionals prioritize its 16.3 TFLOPS FP32 for sustained FP32-heavy computations in CAD or HPC, unavailable at viable scale on the lower-spec RTX 2060.

When to Choose the RTX 2060

The RTX 2060 fits budget-conscious users with cloud pricing from $0.02 per hour, ideal for prototyping small models under 6 GB VRAM or gaming-adjacent inference. Its 160W TDP enables dense deployments in cost-optimized clusters without the Quadro RTX 8000's 260W demands.

Entry-level fine-tuning or Stable Diffusion runs on modest datasets leverage its 6.5 TFLOPS efficiently, especially where live offers average $0.04 per hour.

Use Cases

LLM Training
Quadro RTX 8000

The Quadro RTX 8000's 48 GB VRAM accommodates massive parameter counts, unlike the RTX 2060's 6-12 GB limit. Its 16.3 TFLOPS doubles training speed over the RTX 2060's 6.5 TFLOPS.

LLM Inference
Quadro RTX 8000

48 GB VRAM on the Quadro RTX 8000 supports large batch inference for production LLMs. Bandwidth at 672 GB/s ensures low latency, surpassing the RTX 2060's constraints.

Fine-tuning
Quadro RTX 8000

Fine-tuning mid-sized models benefits from 48 GB VRAM to avoid out-of-memory errors on the RTX 2060's 6-12 GB. NVLink enables efficient scaling.

Stable Diffusion
Quadro RTX 8000

High-resolution image generation demands 48 GB VRAM for complex pipelines, far exceeding the RTX 2060's capacity. 16.3 TFLOPS accelerates diffusion steps.

Scientific Computing
Quadro RTX 8000

Simulations require 672 GB/s bandwidth and 48 GB VRAM for large datasets, where the RTX 2060's 336 GB/s and lower VRAM falter.

Frequently Asked Questions

Which GPU has more VRAM: Quadro RTX 8000 or RTX 2060?

The Quadro RTX 8000 provides 48 GB GDDR6 VRAM. The RTX 2060 offers 6-12 GB GDDR6 VRAM. This makes the Quadro suitable for larger models.

What is the compute performance difference?

Quadro RTX 8000 achieves 16.3 TFLOPS FP16 and FP32. RTX 2060 delivers 6.5 TFLOPS in both. Expect roughly double speed on compute-intensive tasks with the Quadro.

How do power requirements compare?

Quadro RTX 8000 has 260W TDP. RTX 2060 uses 160W TDP. The RTX 2060 suits lower-power cloud instances.

Does RTX 2060 have cloud pricing?

RTX 2060 offers start from $0.02 per hour, averaging $0.04 per hour across 2 providers. Quadro RTX 8000 has no live offers currently.

Which supports multi-GPU better?

Quadro RTX 8000 includes NVLink interconnect. RTX 2060 lacks it, limiting scaling options.

Are both Turing architecture?

Yes, Quadro RTX 8000 uses Turing from 2018. RTX 2060 uses Turing from 2019. They share tensor core capabilities.

Which is cheaper to rent, the Quadro RTX 8000 or the RTX 2060?

Cloud rental prices for both the Quadro RTX 8000 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 Quadro RTX 8000 have compared to the RTX 2060?

The Quadro RTX 8000 has 48 GB of GDDR6 memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.

Can I find Quadro RTX 8000 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 Quadro RTX 8000 and the RTX 2060?

The Quadro RTX 8000 uses the Turing architecture (2018) while the RTX 2060 uses Turing (2019). The Quadro RTX 8000 delivers 2.5x the FP16 throughput and 2.0x the memory bandwidth of the RTX 2060.