GPU Cloud · NVIDIA

Rent NVIDIA GTX 1650 GPU by the hour

The NVIDIA GTX 1650 is an entry-level consumer GPU equipped with 4 GB of VRAM. On ONIE, you can rent this GPU with per-hour billing, SSH access, and ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI. It is suitable for lightweight GPU computing, code testing, and learning environments.

Specifications

VRAM per GPU

4 GB

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

Available configurations

Live stock and prices, updated continuously. The final price is confirmed before you order.

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What the GTX 1650 is good for

CUDA Code Prototyping

Test and debug PyTorch and CUDA scripts on a dedicated consumer GPU before deploying to larger hardware.

Small Model Inference

Run compact machine learning models or tiny quantized language models that fit comfortably within 4 GB of VRAM.

Educational Machine Learning

Train foundational neural networks on small datasets using pre-configured PyTorch/CUDA templates.

Lightweight Media Processing

Execute basic image processing pipelines and low-memory graphics tasks via SSH.

Is it the right GPU for you?

Choose the GTX 1650 if you need an entry-level consumer GPU with 4 GB of VRAM for code verification, learning, or very small workloads. If your tasks involve modern image generation, model fine-tuning, or larger language models, you should select a GPU with more VRAM and higher compute capacity.

Compare with similar GPUs

GPUVRAM per GPUArchitectureFP32 computeFrom / hourDetails
GTX 16504 GB———
GTX 1660 S6 GBTuring≈ 3.6 TFLOPS—Details
GTX 1660 Ti6 GBTuring≈ 5.3 TFLOPS—Details
GTX 1070 Ti8 GBPascal≈ 7.4 TFLOPS—Details

Frequently asked questions

Is the GTX 1650 suitable for LLM inference or image generation?

With 4 GB of VRAM, the GTX 1650 is limited to very compact, heavily quantized language models and basic image tasks. Standard image generation workflows in ComfyUI or larger models in Ollama and vLLM require a GPU with a larger memory capacity.

Can I use the GTX 1650 for model fine-tuning?

The 4 GB memory buffer is generally too small for fine-tuning modern generative models, though it can handle training basic networks on small datasets. For fine-tuning language or diffusion models, a consumer or datacenter GPU with more VRAM is recommended.

How do I connect to the instance and what software is available?

You can connect directly to your instance via SSH access. ONIE provides ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI so you can start working without manual environment setup.

How does billing work for the GTX 1650 on ONIE?

Instances are billed on a per-hour basis. This allows you to rent the GTX 1650 for short development or testing sessions and terminate the instance when your task is complete.

Rent the GTX 1650 by the hour

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

Rent GTX 1650

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