Is the GTX 1080 Ti good for LLMs in 2026?

For quantized 7B–13B models, it works, at moderate speed. It has no Tensor Cores or BF16, so it is not a good choice for fine-tuning or serving many users.

GTX 1080 Ti vs RTX 2080 Ti?

Both have 11 GB. The RTX 2080 Ti is Turing with Tensor Cores, about 14.6 TFLOPS and 501 GB/s, so it is faster and handles FP16 mixed precision far better.

Can it run the latest PyTorch?

Compute capability 6.1 is not targeted by some recent CUDA builds. Check the CUDA and framework versions in your template or Docker image before you deploy.

How is the GTX 1080 Ti billed on Cloudj?

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 · Pascal

Rent an NVIDIA GTX 1080 Ti GPU with 11 GB VRAM

Rent GTX 1080 Ti cloud GPU servers by the hour on Cloudj: 11 GB VRAM, NVIDIA Pascal and about 11 TFLOPS FP32 with 339 GB/s of memory bandwidth. The best-known Pascal card still handles quantized 7B–13B LLMs, SD 1.5 and FP32 workloads for hobbyists and learners at a 250 W power limit. Check that your CUDA and framework versions still support this GPU, pick a live configuration and connect over SSH with your key.

Rent GTX 1080 Ti All GPUs

GTX 1080 Ti specifications

VRAM per GPU

11 GB

Architecture

NVIDIA Pascal

Compute capability

6.1

FP32 compute

≈ 11 TFLOPS

Memory bandwidth

≈ 339 GB/s

Power limit

250 W

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

Live GTX 1080 Ti configurations and prices

Out of stock right now

Browse available GPUs

What you can run on the GTX 1080 Ti cloud GPU

13B models at 4-bit

11 GB fits a 4-bit 13B model or an 8-bit 7B model in Ollama or llama.cpp.

Stable Diffusion 1.5

Generate SD 1.5 images and simple ComfyUI graphs; SDXL works at reduced settings.

FP32 scientific code

11 TFLOPS FP32 is useful for simulations and numerical code that does not need Tensor Cores.

Kaggle-style experiments

Train gradient-boosted trees on GPU and small neural networks for competitions and practice.

Is the GTX 1080 Ti the right GPU for your workload?

Choose the GTX 1080 Ti when you need 11 GB of VRAM for legacy workloads, code testing, or small-scale inference on a Pascal-generation consumer card. Select a newer GPU with more memory for large models or modern mixed-precision workloads, or a smaller consumer GPU if your task requires minimal VRAM.

GTX 1080 Ti vs similar cloud GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA GTX 1080 Ti	11 GB	≈ 11 TFLOPS	250 W
NVIDIA GTX 1080	8 GB	≈ 7.8 TFLOPS	130 W	Details →
NVIDIA GTX 1070 Ti	8 GB	≈ 7.4 TFLOPS	180 W	Details →
NVIDIA GTX 1650	4 GB	≈ undefined TFLOPS	W	Details →
NVIDIA RTX 2080 Ti	11 GB	≈ 14.6 TFLOPS	250 W	Details →

Guides for GTX 1080 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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GTX 1080 Ti cloud GPU: frequently asked questions

Rent the GTX 1080 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 GTX 1080 Ti All GPUs