Rent an NVIDIA RTX A2000 GPU with 6 GB VRAM
Rent RTX A2000 cloud GPU servers by the hour on Cloudj: 6 GB VRAM, Ampere architecture and about 11.2 TFLOPS FP32 at a 70 W power limit. It is a compact professional GPU for developers and learners who need CUDA, light inference or headless video and 3D work rather than a big memory pool. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.
RTX A2000 specifications
VRAM per GPU
6 GB
Architecture
NVIDIA Ampere
Compute capability
8.6
FP32 compute
≈ 11.2 TFLOPS
Memory bandwidth
≈ 247 GB/s
Power limit
70 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live RTX A2000 configurations and prices
From $0.07/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the RTX A2000 cloud GPU
CUDA and PyTorch development
Test code on Ampere (compute capability 8.6) with BF16 support, then move the same environment to a bigger GPU.
Small models and computer vision
Run object detection, OCR, classifiers and 3B-class LLMs at 4-bit in 6 GB.
Video encoding
Encode and transcode video with FFmpeg and NVENC from the command line.
Teaching and workshops
Give students a real Ampere GPU for notebooks and exercises, billed only for the hours used.
Is the RTX A2000 the right GPU for your workload?
Choose the RTX A2000 for low-overhead code debugging, environment setup, and running compact models that fit into 6 GB of VRAM. If your workload involves training, fine-tuning, or running larger unquantized models, select a workstation or datacenter GPU with higher memory capacity and compute throughput.
RTX A2000 vs similar cloud GPUs
Guides for RTX A2000
RTX A2000 cloud GPU: frequently asked questions
Rent the RTX A2000 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.