GPU Cloud · NVIDIA · Ada Lovelace

Rent NVIDIA RTX 4090 GPU by the hour

The NVIDIA RTX 4090 is a consumer-segment GPU built on the Ada Lovelace architecture, available for rent on ONIE. It features 24 GB of VRAM, about 81.4 TFLOPS of standard floating-point compute, and a memory bandwidth of about 879 GB/s. With CUDA compute capability 8.9 and a 450 W power profile, it handles demanding AI and graphics workloads.

Specifications

VRAM per GPU

24 GB

Architecture

NVIDIA Ada Lovelace

Compute capability

8.9

FP32 compute

≈ 81.4 TFLOPS

Memory bandwidth

≈ 879 GB/s

Power limit

450 W

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 RTX 4090 is good for

Local LLM Inference

Run quantized large language models using pre-configured vLLM or Ollama templates within the 24 GB VRAM capacity.

Image Generation and Diffusion

Deploy ComfyUI workflows for high-resolution image synthesis powered by Ada Lovelace compute.

Deep Learning Prototyping

Train and fine-tune medium-sized neural networks using the PyTorch/CUDA template with about 879 GB/s of memory bandwidth.

Graphics Rendering and Simulation

Execute ray-traced rendering and physics simulations utilizing about 81.4 TFLOPS of compute performance.

Is it the right GPU for you?

Choose the RTX 4090 when your workloads need strong Ada Lovelace compute and fit comfortably inside 24 GB of memory. Opt for a smaller consumer GPU for lightweight inference to reduce costs, or step up to a workstation or datacenter GPU when training models that require more than 24 GB of VRAM.

Compare with similar GPUs

GPUVRAM per GPUArchitectureFP32 computeFrom / hourDetails
RTX 409024 GBAda Lovelace≈ 81.4 TFLOPS—
RTX 6000Ada48 GBAda Lovelace≈ 81.4 TFLOPS—Details
RTX 509032 GBBlackwell≈ 107.6 TFLOPS—Details
RTX 5090D32 GBBlackwell≈ 107.6 TFLOPS—Details

Frequently asked questions

Is the RTX 4090 suitable for LLM inference and fine-tuning?

Yes, the 24 GB of VRAM and about 879 GB/s of memory bandwidth make it well-suited for serving small to medium language models and running parameter-efficient fine-tuning. If your model weights and context window exceed 24 GB, you will need a workstation or datacenter GPU with a larger memory capacity.

How do I connect to the RTX 4090 instance and what software is included?

You can connect directly to your instance via SSH access. ONIE provides ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI so you can start working with CUDA compute capability 8.9 right away.

How does the RTX 4090 compare to workstation or datacenter GPUs?

As a consumer-segment card with a 450 W thermal design power, the RTX 4090 delivers high compute density at about 81.4 TFLOPS. However, it caps at 24 GB of VRAM, whereas higher-tier workstation and datacenter GPUs offer larger memory pools for massive datasets.

How does billing work for renting the RTX 4090?

ONIE uses per-hour billing for all GPU rentals. You only pay for the time your instance is active.

Rent the RTX 4090 by the hour

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

Rent RTX 4090

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