GPU Cloud · NVIDIA · Ampere

Rent NVIDIA RTX 3060 laptop GPU by the hour

The NVIDIA RTX 3060 laptop is a consumer-segment GPU built on the Ampere architecture with compute capability 8.6. It provides 12 GB of VRAM, about 12.9 TFLOPS of single-precision compute, and about 299 GB/s of memory bandwidth within an 80 W power envelope. On ONIE, you can rent this GPU with per-hour billing, SSH access, and ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.

Specifications

VRAM per GPU

12 GB

Architecture

NVIDIA Ampere

Compute capability

8.6

FP32 compute

≈ 12.9 TFLOPS

Memory bandwidth

≈ 299 GB/s

Power limit

80 W

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

Available configurations

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What the RTX 3060 laptop is good for

Compact LLM Inference

Run quantized language models that fit within 12 GB of VRAM using pre-configured Ollama or vLLM templates.

Image Generation Workflows

Generate images and test diffusion pipelines using the ComfyUI template on an Ampere consumer GPU.

PyTorch Prototyping and Debugging

Develop and test machine learning code over SSH with the PyTorch/CUDA template and compute capability 8.6 support.

Lightweight Model Fine-Tuning

Perform parameter-efficient fine-tuning on small datasets where 12 GB of memory and about 299 GB/s of bandwidth are sufficient.

Is it the right GPU for you?

Choose the RTX 3060 laptop for entry-level development, testing, and inference workloads that fit into 12 GB of VRAM without needing high power draw. Opt for a larger desktop or datacenter GPU if you need higher memory bandwidth or more VRAM for large models, or a smaller GPU if your workload requires minimal graphics memory.

Compare with similar GPUs

GPUVRAM per GPUArchitectureFP32 computeFrom / hourDetails
RTX 3060 laptop12 GBAmpere≈ 12.9 TFLOPS—
RTX 306012 GBAmpere≈ 12 TFLOPS—Details
Titan Xp12 GBPascal≈ 11.7 TFLOPS—Details
RTX 2080 Ti11 GBTuring≈ 14.6 TFLOPS—Details

Frequently asked questions

Is the RTX 3060 laptop GPU suitable for LLM inference and image generation?

Yes, its 12 GB of VRAM and compute capability 8.6 make it suitable for running smaller quantized language models via Ollama or vLLM, as well as standard diffusion models in ComfyUI. Larger models that exceed 12 GB will require a GPU with a higher memory capacity.

How does this laptop variant compare to desktop GPUs?

As a consumer laptop GPU with an 80 W power limit, it offers about 12.9 TFLOPS of single-precision compute and about 299 GB/s of memory bandwidth, which is lower than full-power desktop or workstation cards. However, its 12 GB VRAM capacity still provides ample room for memory-bound entry-level workloads.

How does billing work on ONIE?

Instances are billed on a per-hour basis, allowing you to pay only for the time your RTX 3060 laptop instance is active.

How do I connect and start my workload?

You can connect directly to your instance via SSH access. ONIE also provides ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI so you can start working immediately.

Rent the RTX 3060 laptop by the hour

Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.

Rent RTX 3060 laptop

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