Rent an NVIDIA RTX 4060 Ti GPU with 16 GB VRAM
Rent RTX 4060 Ti cloud GPU servers by the hour on Cloudj: 16 GB VRAM, Ada Lovelace and about 21.6 TFLOPS FP32 at an efficient 165 W power limit. It is a memory-friendly Ada card for learners and creators who want 16 GB for SDXL, quantized Flux, 14B LLMs at 4-bit and QLoRA on small models. Pick a live configuration, start from the Ubuntu 22.04 + CUDA or PyTorch + JupyterLab template and connect over SSH with your key.
RTX 4060 Ti specifications
VRAM per GPU
16 GB
Architecture
NVIDIA Ada Lovelace
Compute capability
8.9
FP32 compute
≈ 21.6 TFLOPS
Memory bandwidth
≈ 236 GB/s
Power limit
165 W
Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.
Live RTX 4060 Ti configurations and prices
From $0.14/h
incl. 32 GB disk · Live price, updated every 15 minutes
What you can run on the RTX 4060 Ti cloud GPU
SDXL and Flux GGUF
16 GB fits SDXL with LoRAs and quantized Flux in ComfyUI.
14B models at 4-bit
Run 8B at 8-bit or 14B at 4-bit through Ollama for private assistants.
QLoRA on 7B–8B
Fine-tune small LLMs with Unsloth in BF16 within 16 GB.
Efficient batch jobs
A 165 W limit suits long overnight image, embedding or transcription batches.
Is the RTX 4060 Ti the right GPU for your workload?
Pick the RTX 4060 Ti if your workload requires a 16 GB VRAM buffer for model weights on an Ada Lovelace card without needing heavy compute density. Choose a smaller GPU for basic scripts with minimal memory requirements, or step up to a larger consumer or datacenter GPU if your workflow is bottlenecked by the about 236 GB/s memory bandwidth and about 21.6 TFLOPS of compute.
RTX 4060 Ti vs similar cloud GPUs
Guides for RTX 4060 Ti
RTX 4060 Ti cloud GPU: frequently asked questions
Rent the RTX 4060 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.