Rent NVIDIA RTX 4080 GPU by the hour
The NVIDIA RTX 4080 is an Ada Lovelace consumer GPU equipped with 16 GB of VRAM and compute capability 8.9. In our cloud environment, it delivers about 48.6 TFLOPS of single-precision performance and about 576 GB/s of memory bandwidth while operating at a 285 W power rating. You can deploy it on ONIE with per-hour billing, full SSH access, and pre-configured templates.
Specifications
VRAM per GPU
Architecture
Compute capability
FP32 compute
Memory bandwidth
Power limit
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Available configurations
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What the RTX 4080 is good for
Quantized LLM Inference
Run small to medium language models that fit comfortably within 16 GB of VRAM using ready Ollama or vLLM templates.
Image Generation Workflows
Generate high-resolution images and run custom diffusion pipelines using the pre-built ComfyUI template.
Model Prototyping and LoRA
Develop code and run lightweight parameter-efficient fine-tuning jobs on PyTorch/CUDA with Ada Lovelace architecture support.
Batch Data Processing
Utilize about 48.6 TFLOPS of single-precision compute and about 576 GB/s of memory bandwidth for parallel data preprocessing and inference tasks.
Is it the right GPU for you?
The RTX 4080 suits developers who need Ada Lovelace compute capability 8.9 and 16 GB of VRAM for inference, diffusion models, and prototyping. Choose a smaller consumer GPU for basic scripts with lower memory demands, or step up to a higher-VRAM consumer, workstation, or datacenter GPU if your model weights exceed 16 GB.
Compare with similar GPUs
Frequently asked questions
Is the RTX 4080 suitable for LLM inference and fine-tuning?
With 16 GB of VRAM and about 576 GB/s of memory bandwidth, the RTX 4080 handles inference for smaller or quantized language models and lightweight LoRA adapters. Full fine-tuning of large models requires a workstation or datacenter GPU with a larger memory capacity.
How does the RTX 4080 compare to other Ada Lovelace GPUs?
The RTX 4080 sits in the upper consumer segment with 16 GB of VRAM and about 48.6 TFLOPS of single-precision compute. If your workloads are memory-bound or require fitting larger unquantized models into memory, consider moving up to a GPU with more VRAM.
What software templates are available for the RTX 4080 on ONIE?
You can launch an instance with ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. All instances include full SSH access so you can install custom dependencies matching compute capability 8.9.
How does billing work for RTX 4080 instances?
ONIE uses straightforward per-hour billing for all RTX 4080 rentals. You only pay for the time your instance is active.
Rent the RTX 4080 by the hour
Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.
Rent RTX 4080