Rent NVIDIA RTX 5080 GPU by the hour
The NVIDIA RTX 5080 is a consumer-segment GPU built on the Blackwell architecture with compute capability 12.0 and 16 GB of VRAM. On ONIE, it delivers about 53.4 TFLOPS of single-precision compute and a memory bandwidth of about 782 GB/s within a 360 W power envelope. You can deploy it with per-hour billing, direct SSH access, and ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
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
Live stock and prices, updated continuously. The final price is confirmed before you order.
Loading live prices…
What the RTX 5080 is good for
Quantized LLM Inference
Run compact or quantized language models using Ollama or vLLM within the 16 GB VRAM allocation and about 782 GB/s of memory bandwidth.
Generative Image Workflows
Deploy ComfyUI templates to run image generation pipelines utilizing the Blackwell architecture and about 53.4 TFLOPS of compute.
Blackwell Code Development
Test and compile modern kernels targeting compute capability 12.0 in a standard PyTorch/CUDA environment via SSH.
Adapter Fine-Tuning
Perform parameter-efficient fine-tuning on small models where datasets and weights fit inside 16 GB of memory.
Is it the right GPU for you?
Choose the RTX 5080 if you need the Blackwell architecture with compute capability 12.0 and fast memory bandwidth for workloads that fit into 16 GB of VRAM. Opt for a larger workstation or datacenter GPU if your models exceed 16 GB, or select a smaller consumer GPU for basic prototyping with lower compute demands.
Compare with similar GPUs
Frequently asked questions
Is the RTX 5080 suitable for LLM inference and fine-tuning?
With 16 GB of VRAM and about 782 GB/s of memory bandwidth, it handles inference for compact or quantized models via vLLM or Ollama, as well as lightweight adapter fine-tuning. Full fine-tuning of large models requires a GPU with a higher memory capacity.
How does this GPU compare to larger or smaller options?
As a consumer-segment Blackwell card, the RTX 5080 offers compute capability 12.0 and about 53.4 TFLOPS at 360 W, providing more throughput than entry-level consumer cards. However, its 16 GB VRAM ceiling is more restrictive than higher-tier consumer, workstation, or datacenter GPUs designed for massive memory workloads.
What software templates and access methods are included on ONIE?
Instances include full SSH access and can be launched with pre-configured templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. The environment supports workflows targeting compute capability 12.0.
How does billing work for RTX 5080 instances?
Usage on ONIE is billed on a per-hour basis. This allows you to rent the GPU for short testing sessions or extended runs without long-term commitments.
Rent the RTX 5080 by the hour
Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.
Rent RTX 5080