Rent an NVIDIA RTX 4090 GPU with 24 GB VRAM
Rent RTX 4090 cloud GPU servers by the hour on Cloudj: 24 GB VRAM, Ada Lovelace and about 81.4 TFLOPS FP32 with 879 GB/s of memory bandwidth. It is the go-to 24 GB card for AI creators and developers: full-speed Flux and SDXL, 30B-class LLMs at 4-bit, QLoRA fine-tuning and fast rendering, at a 450 W power limit. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.
RTX 4090 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.
Live RTX 4090 configurations and prices
From $0.53/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the RTX 4090 cloud GPU
Flux and SDXL at full speed
81.4 TFLOPS and 24 GB run Flux and SDXL with LoRAs and ControlNets in ComfyUI quickly.
30B-class LLMs at 4-bit
Serve quantized 30B–34B models, or an 8B model in 16-bit, with 879 GB/s for fast decoding.
QLoRA on 7B–14B models
Fine-tune language models with Unsloth in BF16 on one GPU.
Video model workflows
Run 24 GB-class video generation workflows in ComfyUI.
Is the RTX 4090 the right GPU for your workload?
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.
Guides for RTX 4090
RTX 4090 cloud GPU: frequently asked questions
Rent the RTX 4090 cloud GPU by the hour
Pick a live configuration, choose a template and connect over SSH with your key. Billing stops when you destroy the instance.