Īrējiet NVIDIA RTX 4080 GPU pa stundām
The NVIDIA RTX 4080 is an Ada Lovelace consumer GPU equipped with 16 GB of VRAM and compute capability 8.9. In our cloud environment, it delivers about 48.6 TFLOPS of single-precision performance and about 576 GB/s of memory bandwidth while operating at a 285 W power rating. You can deploy it on ONIE with per-hour billing, full SSH access, and pre-configured templates.
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.
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Kam ir piemērots RTX 4080
Quantized LLM Inference
Run small to medium language models that fit comfortably within 16 GB of VRAM using ready Ollama or vLLM templates.
Image Generation Workflows
Generate high-resolution images and run custom diffusion pipelines using the pre-built ComfyUI template.
Model Prototyping and LoRA
Develop code and run lightweight parameter-efficient fine-tuning jobs on PyTorch/CUDA with Ada Lovelace architecture support.
Batch Data Processing
Utilize about 48.6 TFLOPS of single-precision compute and about 576 GB/s of memory bandwidth for parallel data preprocessing and inference tasks.
Vai tas ir piemērots GPU Jums?
The RTX 4080 suits developers who need Ada Lovelace compute capability 8.9 and 16 GB of VRAM for inference, diffusion models, and prototyping. Choose a smaller consumer GPU for basic scripts with lower memory demands, or step up to a higher-VRAM consumer, workstation, or datacenter GPU if your model weights exceed 16 GB.
Salīdzināt ar līdzīgiem GPU
Biežāk uzdotie jautājumi
Is the RTX 4080 suitable for LLM inference and fine-tuning?
With 16 GB of VRAM and about 576 GB/s of memory bandwidth, the RTX 4080 handles inference for smaller or quantized language models and lightweight LoRA adapters. Full fine-tuning of large models requires a workstation or datacenter GPU with a larger memory capacity.
How does the RTX 4080 compare to other Ada Lovelace GPUs?
The RTX 4080 sits in the upper consumer segment with 16 GB of VRAM and about 48.6 TFLOPS of single-precision compute. If your workloads are memory-bound or require fitting larger unquantized models into memory, consider moving up to a GPU with more VRAM.
What software templates are available for the RTX 4080 on ONIE?
You can launch an instance with ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. All instances include full SSH access so you can install custom dependencies matching compute capability 8.9.
How does billing work for RTX 4080 instances?
ONIE uses straightforward per-hour billing for all RTX 4080 rentals. You only pay for the time your instance is active.
Nomājiet RTX 4080 pa stundām
Izveidojiet kontu, izvēlieties konfigurāciju un pieslēdzieties caur SSH. Norēķini tiek pārtraukti, kad dzēšat GPU.
Nomāt RTX 4080