Rent an NVIDIA GTX 1070 Ti GPU with 8 GB VRAM
Rent GTX 1070 Ti cloud GPU servers by the hour on Cloudj: 8 GB VRAM, NVIDIA Pascal and about 7.4 TFLOPS FP32 for learning CUDA and light inference. It is a low-commitment card for students, hobbyists and developers testing scripts, small models and SD 1.5 before paying for newer hardware (193 GB/s, 180 W). Check that your CUDA and framework versions still support this GPU, pick a live configuration and connect over SSH with your key.
GTX 1070 Ti specifications
VRAM per GPU
8 GB
Architecture
NVIDIA Pascal
Compute capability
6.1
FP32 compute
≈ 7.4 TFLOPS
Memory bandwidth
≈ 193 GB/s
Power limit
180 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live GTX 1070 Ti configurations and prices
Out of stock right now
Browse available GPUsWhat you can run on the GTX 1070 Ti cloud GPU
Learn CUDA and GPU Linux
Practice drivers, nvidia-smi, CUDA builds and PyTorch basics on a real GPU server without buying one.
Small quantized LLMs
Run 3B–7B GGUF models at 4-bit in Ollama for experiments and offline-style chat.
SD 1.5 image generation
8 GB runs Stable Diffusion 1.5 in FP32 at standard resolutions; expect slower images than on RTX cards.
Classic computer vision
Train or run CNN classifiers, detectors and OCR models on small datasets.
Is the GTX 1070 Ti the right GPU for your workload?
Choose the GTX 1070 Ti for lightweight development, educational projects, and inference workloads that comfortably fit into 8 GB of VRAM and run on compute capability 6.1. Opt for a GPU with more VRAM and a newer architecture if you need to fine-tune large models, or select a smaller GPU if you only require minimal display or basic compute tasks.
Guides for GTX 1070 Ti
GTX 1070 Ti cloud GPU: frequently asked questions
Rent the GTX 1070 Ti 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.