Rent an NVIDIA A100 SXM4 GPU with 40 GB VRAM
Rent A100 SXM4 GPUs by the hour on Cloudj: 40 GB VRAM on NVIDIA Ampere with about 1313 GB/s memory bandwidth and a 400 W power limit for sustained AI work. Built for teams that run long training or serving jobs and want the SXM module's thermal headroom, it offers 15.6 TFLOPS FP32 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 SXM4 specifications
VRAM per GPU
40 GB
Architecture
NVIDIA Ampere
Compute capability
8
FP32 compute
≈ 15.6 TFLOPS
Memory bandwidth
≈ 1313 GB/s
Power limit
400 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live A100 SXM4 configurations and prices
From $0.46/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the A100 SXM4 cloud GPU
Long-running training jobs
The 400 W power limit suits multi-hour BF16 training where clocks have to hold steady from the first epoch to the last.
Production-style LLM serving
Host a 13B model in 16-bit or a quantized 30B-class model behind vLLM or SGLang and test throughput before you commit to infrastructure.
Instruction tuning with Unsloth
Run LoRA or QLoRA on 7B–13B models with longer sequences than a 24 GB card allows.
Research reproduction
Reproduce papers that were benchmarked on A100-class hardware on the same Ampere architecture and memory size.
Is the A100 SXM4 the right GPU for your workload?
Choose the 40 GB A100 SXM4 when your training or inference workloads exceed consumer GPU memory limits and require datacenter memory bandwidth. Opt for a higher-VRAM datacenter GPU if your unquantized models exceed 40 GB, or select a smaller workstation or consumer card for lightweight inference and development.
Guides for A100 SXM4
A100 SXM4 cloud GPU: frequently asked questions
Rent the A100 SXM4 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.