RTX 2060S vs RTX 2060 (12 GB)?

The RTX 2060S has more bandwidth (370 vs 268 GB/s) and slightly more FP32 (7.5 vs 6.5 TFLOPS), but only 8 GB versus 12 GB. If your model barely fits, the 12 GB RTX 2060 wins.

Can the RTX 2060S run SDXL?

With memory-saving options and patience. SDXL is much smoother on 12 GB or more, such as the RTX 3060 or RTX 4070.

Does it support BF16?

No, Turing supports FP16 Tensor Core math but not BF16. Recipes that require BF16 need an Ampere or newer GPU.

What happens if I stop my RTX 2060S on Cloudj?

Only storage is charged while it is stopped, and your files stay until you destroy the instance. Stopping releases the GPU, so starting again may wait until it is free.

GPU Cloud · NVIDIA · Turing

Rent an NVIDIA RTX 2060S GPU with 8 GB VRAM

Rent RTX 2060S cloud GPU servers by the hour on Cloudj: 8 GB VRAM on NVIDIA Turing with about 7.5 TFLOPS FP32 and 370 GB/s of memory bandwidth. It suits learners and developers who need Tensor Cores for small FP16 jobs, SD 1.5 images and 7B models at 4-bit, at a 175 W power limit. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.

Rent RTX 2060S All GPUs

RTX 2060S specifications

VRAM per GPU

8 GB

Architecture

NVIDIA Turing

Compute capability

7.5

FP32 compute

≈ 7.5 TFLOPS

Memory bandwidth

≈ 370 GB/s

Power limit

175 W

Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.

Live RTX 2060S configurations and prices

Out of stock right now

Browse available GPUs

What you can run on the RTX 2060S cloud GPU

SD 1.5 generation

8 GB and Turing Tensor Cores run Stable Diffusion 1.5 in FP16 at standard resolutions.

7B LLMs at 4-bit

Serve 7B–8B models quantized to 4 bits in Ollama for prompt testing.

Small FP16 training

Train small CNNs and transformers with mixed precision to learn modern training loops.

Inference APIs for prototypes

Wrap a small model in an API and test integration before moving to a bigger GPU.

Is the RTX 2060S the right GPU for your workload?

Choose the RTX 2060S for entry-level development, testing, and lightweight inference tasks that fit comfortably into 8 GB of memory. Opt for a GPU with more VRAM and higher compute if you need to fine-tune large models or run heavy production workloads, or a smaller GPU only for basic display or minimal compute tasks.

RTX 2060S vs similar cloud GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA RTX 2060S	8 GB	≈ 7.5 TFLOPS	175 W
NVIDIA GTX 1070 Ti	8 GB	≈ 7.4 TFLOPS	180 W	Details →
NVIDIA GTX 1080	8 GB	≈ 7.8 TFLOPS	130 W	Details →
NVIDIA GTX 1660 Ti	6 GB	≈ 5.3 TFLOPS	120 W	Details →
NVIDIA GTX 1080 Ti	11 GB	≈ 11 TFLOPS	250 W	Details →

Guides for RTX 2060S

GPU cloud Asia guide: Japan, Singapore, Korea and nearbyA practical GPU cloud Asia guide: which country codes to search for East and Southeast Asian users, a fallback order, and how to pair a GPU with a VPS.GPU cloud by location: how to pick a country for your GPUHow GPU cloud by location works on Cloudj: filter a live list of machines by country code, decide between near users, lowest price or data rules.GPU cloud Europe: choosing a country for your AI workloadsA practical guide to GPU cloud Europe searches: filter by several country codes at once, weigh Western, Nordic and Eastern hosts, and plan where data lives.GPU cloud North America: renting GPUs in the US and CanadaA GPU cloud North America guide: how to search US and CA hosts, read the results, pick a VPS front end and decide when a US GPU suits users elsewhere.

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RTX 2060S cloud GPU: frequently asked questions

Rent the RTX 2060S cloud GPU by the hour

Pick a live configuration, choose a template and connect over SSH with your key. Billing stops when you destroy the instance.

Rent RTX 2060S All GPUs