Īrējiet NVIDIA RTX 4070S GPU pa stundām
The NVIDIA RTX 4070S is a consumer-segment GPU built on the Ada Lovelace architecture with CUDA compute capability 8.9. Available to rent on ONIE, it equips your environment with 12 GB of VRAM, about 35.8 TFLOPS of standard floating-point compute, and a memory bandwidth of about 411 GB/s. Operating at a 220 W TDP, this card handles mid-sized generative AI and development tasks with per-hour billing and full SSH access.
Specifikācijas
VRAM katram GPU
Arhitektūra
Skaitļošanas spēja
FP32 skaitļošana
Atmiņas joslas platums
Jaudas ierobežojums
Vērtības, ko par pašlaik piedāvātajiem serveriem norādījis infrastruktūras nodrošinātājs; reālā veiktspēja dažādos serveros var atšķirties.
Pieejamās konfigurācijas
Aktuālie krājumi un cenas, kas tiek atjaunotas nepārtraukti. Galīgā cena tiek apstiprināta pirms pasūtīšanas.
Ielādē aktuālās cenas…
Kam ir piemērots RTX 4070S
Quantized LLM Inference
Run compact or quantized language models within the 12 GB VRAM allocation using pre-configured Ollama or vLLM templates.
Diffusion Image Generation
Generate and iterate on visual assets with ComfyUI, utilizing the Ada Lovelace architecture and about 35.8 TFLOPS of compute.
PyTorch Model Prototyping
Develop, test, and debug deep learning code using the ready PyTorch/CUDA template on hardware supporting compute capability 8.9.
Fine-Tuning Small Models
Execute parameter-efficient fine-tuning jobs and lightweight training runs that fit comfortably inside a 12 GB memory ceiling.
Vai tas ir piemērots GPU Jums?
Choose the RTX 4070S when your workloads require modern Ada Lovelace features and compute capability 8.9 within a 12 GB memory envelope. Opt for a smaller GPU for basic scripts and very light inference, or step up to a larger workstation or datacenter GPU if your models exceed 12 GB of VRAM or require higher than about 411 GB/s of memory bandwidth.
Salīdzināt ar līdzīgiem GPU
Biežāk uzdotie jautājumi
Is the RTX 4070S suitable for LLM inference and image generation?
Yes, the 12 GB of VRAM and about 411 GB/s of memory bandwidth handle compact or quantized language models and standard diffusion workflows well. You can deploy these workloads directly on ONIE using ready templates for Ollama, vLLM, and ComfyUI.
How does this GPU compare to larger or smaller options?
As a 12 GB consumer-segment card, the RTX 4070S offers more memory headroom and compute than entry-level GPUs while maintaining a modest 220 W TDP. However, if you are training large networks or running unquantized models that exceed 12 GB, you should select a higher-tier consumer or workstation GPU with a larger memory capacity.
What software templates and access methods are included?
Every instance on ONIE includes direct SSH access so you can manage your environment from your terminal. You can also launch instances with pre-configured templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
How does billing work for the RTX 4070S on ONIE?
Instances are billed on a per-hour basis, allowing you to pay only for the time your GPU is active. You can spin up an environment for a short prototyping session and terminate it when your job finishes.
Nomājiet RTX 4070S pa stundām
Izveidojiet kontu, izvēlieties konfigurāciju un pieslēdzieties caur SSH. Norēķini tiek pārtraukti, kad dzēšat GPU.
Nomāt RTX 4070S