RTX 2080 Ti vs RTX 3080?

The RTX 3080 is Ampere with 10 GB, about 29.5 TFLOPS and 656 GB/s, so it is about twice as fast in FP32. The RTX 2080 Ti has 1 GB more memory (11 GB).

Is the RTX 2080 Ti still good for AI?

Yes for inference and small training jobs that fit in 11 GB. It lacks BF16, so some recent fine-tuning recipes need FP16 settings instead.

Can I run SDXL on 11 GB?

Yes with FP16 and modest add-ons. For Flux or heavy SDXL graphs, a 16–24 GB card is more comfortable.

How does Cloudj bill the RTX 2080 Ti?

Per minute from your account balance while it runs, at the price locked when you deploy, plus bandwidth per GB. A stopped instance is charged for storage only. There are no monthly GPU plans.

GPU Cloud · NVIDIA · Turing

Rent an NVIDIA RTX 2080 Ti GPU with 11 GB VRAM

Name: NVIDIA RTX 2080 Ti cloud GPU
Brand: Cloudj
Availability: InStock

Rent RTX 2080 Ti cloud GPU servers by the hour on Cloudj: 11 GB VRAM, NVIDIA Turing and about 14.6 TFLOPS FP32 with 501 GB/s of memory bandwidth. It is the top Turing consumer card, a practical choice for developers running 13B LLMs at 4-bit, SD 1.5 and SDXL, and FP16 training at a 250 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 2080 Ti All GPUs

RTX 2080 Ti specifications

VRAM per GPU

11 GB

Architecture

NVIDIA Turing

Compute capability

7.5

FP32 compute

≈ 14.6 TFLOPS

Memory bandwidth

≈ 501 GB/s

Power limit

250 W

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

Live RTX 2080 Ti configurations and prices

From $0.10/h

incl. 32 GB disk · Live price, updated every 15 minutes

Deploy

What you can run on the RTX 2080 Ti cloud GPU

13B models at 4-bit

11 GB holds a 4-bit 13B model or an 8-bit 7B model, and 501 GB/s keeps responses quick.

SDXL with memory tweaks

Run SDXL in ComfyUI with FP16 and a light set of add-ons.

FP16 training

Turing Tensor Cores and 14.6 TFLOPS FP32 make it a capable card for small and mid-size training runs.

Inference benchmarking

Compare engines like vLLM, llama.cpp and TensorRT on a known Turing baseline.

Is the RTX 2080 Ti the right GPU for your workload?

Pick the RTX 2080 Ti for development, inference on smaller models, and moderate training tasks that fit within 11 GB of VRAM. Choose a GPU with more memory and newer architecture for large-scale training or unquantized models, or step down to a smaller consumer card for basic debugging.

RTX 2080 Ti vs similar cloud GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA RTX 2080 Ti	11 GB	≈ 14.6 TFLOPS	250 W
NVIDIA GTX 1080 Ti	11 GB	≈ 11 TFLOPS	250 W	Details →
NVIDIA RTX 3060 laptop	12 GB	≈ 12.9 TFLOPS	80 W	Details →
NVIDIA RTX 3060	12 GB	≈ 12 TFLOPS	170 W	Details →
NVIDIA Titan Xp	12 GB	≈ 11.7 TFLOPS	160 W	Details →

Guides for RTX 2080 Ti

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 2080 Ti cloud GPU: frequently asked questions

Rent the RTX 2080 Ti 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 2080 Ti All GPUs