GPU Cloud · NVIDIA · Ampere

Iznajmite NVIDIA RTX 3090 GPU po satu

The NVIDIA RTX 3090 is an Ampere-architecture consumer GPU equipped with 24 GB of VRAM and compute capability 8.6. It delivers about 35.4 TFLOPS of standard single-precision compute and about 805 GB/s of memory bandwidth at a 350 W power rating. You can rent this GPU on ONIE with per-hour billing, full SSH access, and ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI.

Specifikacije

VRAM po GPU-u

24 GB

Arhitektura

NVIDIA Ampere

Računalna sposobnost

8.6

FP32 računanje

≈ 35.4 TFLOPS

Propusnost memorije

≈ 805 GB/s

Ograničenje snage

350 W

Vrijednosti koje je navela infrastrukturna platforma za trenutno navedene strojeve; stvarne performanse razlikuju se ovisno o stroju.

Dostupne konfiguracije

Zalihe i cijene u stvarnom vremenu, neprekidno ažurirane. Konačnu cijenu potvrđujemo prije narudžbe.

Učitavanje cijena u stvarnom vremenu…

Za što je RTX 3090 pogodan

Local-scale LLM inference

Run quantized or mid-sized language models in 24 GB of VRAM using pre-configured vLLM or Ollama templates.

Image generation workflows

Deploy ComfyUI to generate high-resolution images and run custom diffusion pipelines without hitting memory limits on standard consumer cards.

Model fine-tuning and training

Use the PyTorch/CUDA template to fine-tune neural networks that fit within a 24 GB memory envelope and leverage about 805 GB/s of memory bandwidth.

General CUDA compute

Execute custom workloads compiled for compute capability 8.6 with about 35.4 TFLOPS of single-precision performance.

Je li to pravi GPU za vas?

The RTX 3090 suits developers and researchers who need 24 GB of VRAM for memory-intensive tasks on a consumer-segment Ampere card. Choose a smaller GPU for lightweight inference that requires less memory, or step up to a workstation or datacenter GPU if your models exceed 24 GB of VRAM or require newer architecture features.

Usporedite sa sličnim GPU-ovima

GPUVRAM po GPU-uArhitekturaFP32 računanjeOd / satPojedinosti
RTX 309024 GBAmpere≈ 35.4 TFLOPS—
RTX 3090 Ti24 GBAmpere≈ 36.4 TFLOPS—Pojedinosti
RTX 4500Ada24 GBAda Lovelace≈ 38.2 TFLOPS—Pojedinosti
RTX PRO 400024 GBBlackwell≈ 44.3 TFLOPS—Pojedinosti

Često postavljana pitanja

Is the RTX 3090 suitable for LLM inference and fine-tuning?

Yes, its 24 GB of VRAM and about 805 GB/s of memory bandwidth make it capable of running and fine-tuning many open-weight language models. You can launch vLLM, Ollama, or PyTorch/CUDA templates directly on ONIE to start working immediately.

How does the RTX 3090 compare to smaller or larger GPUs?

With 24 GB of VRAM, the RTX 3090 holds significantly more model weights and larger batch sizes than lower-tier consumer cards. However, if your workload requires more than 24 GB of memory or higher than about 35.4 TFLOPS of single-precision compute, you should consider a newer generation or a datacenter-segment GPU.

How do I connect to my RTX 3090 instance and what software is included?

You can connect directly to your instance via SSH access. ONIE provides ready-to-use templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI so you do not have to configure the software stack manually.

How does billing work for the RTX 3090 on ONIE?

Instances are billed on a per-hour basis. You only pay for the time your GPU instance is active.

Iznajmite RTX 3090 po satu

Stvorite račun, odaberite konfiguraciju i povežite se putem SSH-a. Naplata prestaje kada izbrišete GPU.

Iznajmi RTX 3090

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