RTX 3060 vs RTX 3060 Ti: which is better for AI?

The RTX 3060 Ti is faster (about 15.7 vs 12 TFLOPS) but has only 8 GB. The RTX 3060 has 12 GB, which fits SDXL, 13B models at 4-bit and small fine-tunes that the Ti cannot.

Can the RTX 3060 run Flux?

Yes, using quantized GGUF or FP8 versions in ComfyUI, at slower speeds than high-end cards. Full 16-bit Flux needs 24 GB or more.

Can I fine-tune an LLM on 12 GB?

QLoRA on 7B–8B models with short sequences works with Unsloth. For longer sequences or 13B models, step up to a 16–24 GB card.

How do I rent an RTX 3060 on Cloudj?

Choose a template, pick a live RTX 3060 configuration (filter by country if location matters), select your SSH key and confirm the price. Then connect over SSH with the host and port shown on the instance page.

GPU Cloud · NVIDIA · Ampere

Rent an NVIDIA RTX 3060 GPU with 12 GB VRAM

Name: NVIDIA RTX 3060 cloud GPU
Brand: Cloudj
Availability: InStock

Rent RTX 3060 cloud GPU servers by the hour on Cloudj: 12 GB VRAM, NVIDIA Ampere and about 12 TFLOPS FP32 with BF16 support at a 170 W power limit. It is the entry point for modern AI on a budget: SDXL, Flux in quantized form, 8B LLMs at 8-bit and QLoRA on small models for learners and indie builders. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.

Rent RTX 3060 All GPUs

RTX 3060 specifications

VRAM per GPU

12 GB

Architecture

NVIDIA Ampere

Compute capability

8.6

FP32 compute

≈ 12 TFLOPS

Memory bandwidth

≈ 318 GB/s

Power limit

170 W

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

Live RTX 3060 configurations and prices

From $0.09/h

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

Deploy

What you can run on the RTX 3060 cloud GPU

SDXL and quantized Flux

12 GB runs SDXL with LoRAs and Flux in GGUF form in ComfyUI.

8B LLMs for private chat

Run an 8B model at 8-bit or a 14B model at 4-bit with Ollama and Open WebUI.

QLoRA on 3B–8B models

Fine-tune small language models with Unsloth in BF16 on Ampere.

Train your first LoRA

Create SD 1.5 or SDXL LoRAs on your own image set without buying a GPU.

Is the RTX 3060 the right GPU for your workload?

Choose the RTX 3060 for development, prototyping, and lightweight inference tasks that require 12 GB of VRAM without the expense of datacenter hardware. Opt for a larger GPU if your models exceed 12 GB or require higher memory bandwidth than about 318 GB/s, or a smaller GPU if you only run minimal scripts with lower memory demands.

RTX 3060 vs similar cloud GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA RTX 3060	12 GB	≈ 12 TFLOPS	170 W
NVIDIA GTX 1080 Ti	11 GB	≈ 11 TFLOPS	250 W	Details →
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 →

Guides for RTX 3060

GPU CI runner for ML projects: tests on rented GPU machinesSet up a GPU CI runner pattern for ML tests: a CI runner on a VPS calls a short-lived GPU instance over SSH, billing runs per minute and you destroy it after.Rent an RTX 3060 cheaply: a 12 GB starter GPU for learnersRent an RTX 3060 cheaply as a 12 GB starter GPU: what it runs, how it compares with the 3060 Ti and 4060 Ti, and how to find a low price near Vietnam.Jupyter notebook GPU for students: a low-cost cloud setupA Jupyter notebook GPU setup for students on a small budget: pick a small RTX card, use per-minute billing well, and save your notebooks before you destroy.Stable Diffusion GPU rental for Vietnamese users: a guideA practical Stable Diffusion GPU rental workflow for Vietnamese designers and shops: pick a 12-24 GB card near Vietnam, pay in VND and move images efficiently.

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RTX 3060 cloud GPU: frequently asked questions

Rent the RTX 3060 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 3060 All GPUs