Is the RTX 4070S Ti suitable for LLM inference and fine-tuning?

With 16 GB of VRAM and about 586 GB/s of memory bandwidth, it handles inference for smaller or quantized language models and parameter-efficient fine-tuning like LoRA. Full fine-tuning of larger models will require a GPU with more memory.

How does the RTX 4070S Ti compare to smaller or larger GPUs?

As a 16 GB Ada Lovelace consumer card delivering about 42.6 TFLOPS at 285 W, it offers more memory capacity than entry-level consumer cards from the same generation. However, it has less VRAM and memory bandwidth than higher-end consumer or workstation GPUs.

What software templates are available on Cloudj for this GPU?

You can launch the RTX 4070S Ti with ready-to-use templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. All instances include full SSH access so you can customize your environment.

How does billing work when renting an RTX 4070S Ti?

Cloudj uses per-hour billing for all GPU instances. You only pay for the time your instance is active, making it practical for short experiments or ongoing development sessions.

GPU Cloud · NVIDIA · Ada Lovelace

Rent NVIDIA RTX 4070S Ti GPU by the hour

The NVIDIA RTX 4070S Ti is an Ada Lovelace consumer GPU equipped with 16 GB of VRAM and compute capability 8.9. Infrastructure providers report about 42.6 TFLOPS of standard floating-point performance and about 586 GB/s of memory bandwidth within a 285 W power envelope. On Cloudj, you can rent this GPU with per-hour billing, full SSH access, and ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.

Rent RTX 4070S Ti All GPUs

Specifications

VRAM per GPU

16 GB

Architecture

NVIDIA Ada Lovelace

Compute capability

8.9

FP32 compute

≈ 42.6 TFLOPS

Memory bandwidth

≈ 586 GB/s

Power limit

285 W

Values reported by the infrastructure provider for machines currently listed; real performance varies by machine.

Available configurations

Live stock and prices, updated continuously. The final price is confirmed before you order.

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What the RTX 4070S Ti is good for

Local-scale LLM inference

Run quantized open-weight language models that fit comfortably within 16 GB of VRAM using pre-configured Ollama or vLLM templates.

Diffusion image generation

Generate and iterate on high-resolution images with ComfyUI, utilizing the Ada Lovelace architecture and about 586 GB/s of memory bandwidth.

LoRA and adapter fine-tuning

Train lightweight adapters and smaller neural networks in PyTorch on a GPU supporting compute capability 8.9.

CUDA development and prototyping

Write, debug, and test custom kernels via SSH before deploying workloads to larger datacenter hardware.

Is it the right GPU for you?

Choose the RTX 4070S Ti if your workloads require compute capability 8.9 and fit into 16 GB of VRAM without needing enterprise-grade memory capacity. Opt for a smaller consumer GPU for basic development tasks with lighter memory needs, or step up to a larger consumer or workstation card if your models exceed 16 GB.

Compare with similar GPUs

GPU	VRAM per GPU	FP32 compute	Power limit
NVIDIA RTX 4070S Ti	16 GB	≈ 42.6 TFLOPS	285 W
NVIDIA RTX 5070 Ti	16 GB	≈ 44.3 TFLOPS	300 W	Details →
NVIDIA RTX 4060 Ti	16 GB	≈ 21.6 TFLOPS	165 W	Details →
NVIDIA RTX 3080 Ti	12 GB	≈ 35.1 TFLOPS	350 W	Details →
NVIDIA GTX 1080 Ti	11 GB	≈ 11 TFLOPS	250 W	Details →

Frequently asked questions

Rent the RTX 4070S Ti by the hour

Create an account, choose a configuration and connect over SSH. Billing stops when you delete the GPU.

Rent RTX 4070S Ti All GPUs