Rent an NVIDIA RTX 6000Ada GPU with 48 GB VRAM
Rent RTX 6000Ada cloud GPU servers by the hour on Cloudj: 48 GB VRAM, Ada Lovelace and about 81.4 TFLOPS FP32 with 764 GB/s of memory bandwidth. It combines flagship Ada compute with double the memory of an RTX 4090, ideal for generative AI, large renders and 30B–70B quantized LLMs at a 300 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 6000Ada specifications
VRAM per GPU
48 GB
Architecture
NVIDIA Ada Lovelace
Compute capability
8.9
FP32 compute
≈ 81.4 TFLOPS
Memory bandwidth
≈ 764 GB/s
Power limit
300 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live RTX 6000Ada configurations and prices
From $0.82/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the RTX 6000Ada cloud GPU
70B LLMs at 4-bit
48 GB fits a 4-bit 70B model with a modest context, or a 30B-class model at 8-bit with room to spare.
Full-precision Flux and video
Run Flux in 16-bit and memory-hungry video workflows in ComfyUI without offloading.
Fine-tuning 13B–34B models
QLoRA on 30B-class models and LoRA on 13B models in BF16 fit on a single card with Unsloth.
Production-quality rendering
81.4 TFLOPS FP32 and 48 GB handle complex scenes, heavy textures and final-frame renders.
Is the RTX 6000Ada the right GPU for your workload?
Choose the RTX 6000Ada when your workload exceeds consumer GPU memory limits and requires 48 GB of VRAM alongside Ada Lovelace architectural features. Opt for a smaller consumer GPU for lightweight inference, or step up to a high-memory datacenter GPU if your models require even greater memory capacity or higher memory bandwidth than about 764 GB/s.
RTX 6000Ada vs similar cloud GPUs
Guides for RTX 6000Ada
RTX 6000Ada cloud GPU: frequently asked questions
Rent the RTX 6000Ada 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.