Rent an NVIDIA A100 PCIE GPU with 40 GB VRAM
Rent A100 PCIE cloud GPU servers by the hour on Cloudj: 40 GB VRAM, Ampere architecture and about 1313 GB/s of memory bandwidth for LLM and training jobs. It is the practical datacenter step for ML engineers whose models no longer fit on a gaming card, with 15.6 TFLOPS FP32, a 250 W power limit and compute capability 8.0. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.
A100 PCIE specifications
VRAM per GPU
40 GB
Architecture
NVIDIA Ampere
Compute capability
8
FP32 compute
≈ 15.6 TFLOPS
Memory bandwidth
≈ 1313 GB/s
Power limit
250 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live A100 PCIE configurations and prices
From $0.50/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the A100 PCIE cloud GPU
Serve 13B–34B models with vLLM
40 GB holds a 13B model in 16-bit or a quantized 30B-class model, and 1313 GB/s keeps token generation moving under concurrent requests.
LoRA and QLoRA fine-tuning
Fine-tune 7B–13B language models on your own data with Unsloth or plain PyTorch in BF16, without squeezing batch size to fit.
Mixed-precision training runs
Train vision, speech or tabular models in BF16 on a stable datacenter card instead of renting a full multi-GPU node.
Embeddings and batch inference
Push large document sets through embedding or classification models overnight and delete the server when the batch is done.
Is the A100 PCIE the right GPU for your workload?
Choose the A100 PCIE 40 GB when your workloads exceed the memory limits of consumer GPUs and require high-bandwidth datacenter hardware. Opt for a smaller consumer GPU for lightweight inference, or step up to a higher-VRAM datacenter model if your unquantized models or batch sizes exceed 40 GB.
Guides for A100 PCIE
A100 PCIE cloud GPU: frequently asked questions
Rent the A100 PCIE 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.