RTX 2070 vs RTX 2070S?

Both have 8 GB. The RTX 2070S is listed with about 8.8 TFLOPS at 210 W versus 7.7 TFLOPS at 150 W here, a modest step up in compute.

Is 8 GB enough for LLMs?

For 7B–8B models at 4-bit, yes, with a moderate context. 13B models or 8-bit 8B models need 12 GB or more.

RTX 2070 vs RTX 3060 Ti?

Both have 8 GB. The RTX 3060 Ti is Ampere with about 15.7 TFLOPS, double the RTX 2070's FP32, plus BF16 support.

How is the RTX 2070 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 · Turing

Rent an NVIDIA RTX 2070 GPU with 8 GB VRAM

Rent RTX 2070 cloud GPU servers by the hour on Cloudj: 8 GB VRAM, NVIDIA Turing and about 7.7 TFLOPS FP32 at a 150 W power limit. It is a dependable 8 GB card for learners, indie developers and small teams running SD 1.5, quantized 7B LLMs and FP16 experiments with Tensor Cores. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.

Rent RTX 2070 All GPUs

RTX 2070 specifications

VRAM per GPU

8 GB

Architecture

NVIDIA Turing

Compute capability

7.5

FP32 compute

≈ 7.7 TFLOPS

Memory bandwidth

≈ 370 GB/s

Power limit

150 W

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

Live RTX 2070 configurations and prices

Out of stock right now

Browse available GPUs

What you can run on the RTX 2070 cloud GPU

Stable Diffusion 1.5 images

Generate SD 1.5 images in ComfyUI with Tensor Core FP16 acceleration.

Quantized LLM chat

Run 7B–8B models at 4-bit in Ollama with Open WebUI for a private assistant.

Mixed-precision experiments

Test FP16 training scripts on Turing before running them on larger GPUs.

Headless media work

Encode video with FFmpeg or render light 3D scenes in batch mode over SSH.

Is the RTX 2070 the right GPU for your workload?

Choose the RTX 2070 for lightweight development, code debugging, and small-scale inference tasks that fit comfortably within 8 GB of VRAM. Opt for a larger GPU if your models require more memory or higher throughput than about 7.7 TFLOPS, or select a smaller GPU only for minimal display or basic compute testing.

RTX 2070 vs similar cloud GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA RTX 2070	8 GB	≈ 7.7 TFLOPS	150 W
NVIDIA GTX 1080	8 GB	≈ 7.8 TFLOPS	130 W	Details →
NVIDIA RTX 2060S	8 GB	≈ 7.5 TFLOPS	175 W	Details →
NVIDIA GTX 1070 Ti	8 GB	≈ 7.4 TFLOPS	180 W	Details →
NVIDIA RTX 2070S	8 GB	≈ 8.8 TFLOPS	210 W	Details →

Guides for RTX 2070

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 2070 cloud GPU: frequently asked questions

Rent the RTX 2070 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 2070 All GPUs