GPU Cloud · NVIDIA · Blackwell

Închiriați GPU NVIDIA RTX 5080 pe oră

The NVIDIA RTX 5080 is a consumer-segment GPU built on the Blackwell architecture with compute capability 12.0 and 16 GB of VRAM. On ONIE, it delivers about 53.4 TFLOPS of single-precision compute and a memory bandwidth of about 782 GB/s within a 360 W power envelope. You can deploy it with per-hour billing, direct SSH access, and ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.

Specificații

VRAM per GPU

16 GB

Arhitectură

NVIDIA Blackwell

Capacitate de calcul

12.0

Calcul FP32

≈ 53.4 TFLOPS

Lățime de bandă a memoriei

≈ 782 GB/s

Limită de putere

360 W

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Configurații disponibile

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Pentru ce este potrivit RTX 5080

Quantized LLM Inference

Run compact or quantized language models using Ollama or vLLM within the 16 GB VRAM allocation and about 782 GB/s of memory bandwidth.

Generative Image Workflows

Deploy ComfyUI templates to run image generation pipelines utilizing the Blackwell architecture and about 53.4 TFLOPS of compute.

Blackwell Code Development

Test and compile modern kernels targeting compute capability 12.0 in a standard PyTorch/CUDA environment via SSH.

Adapter Fine-Tuning

Perform parameter-efficient fine-tuning on small models where datasets and weights fit inside 16 GB of memory.

Este GPU-ul potrivit pentru dumneavoastră?

Choose the RTX 5080 if you need the Blackwell architecture with compute capability 12.0 and fast memory bandwidth for workloads that fit into 16 GB of VRAM. Opt for a larger workstation or datacenter GPU if your models exceed 16 GB, or select a smaller consumer GPU for basic prototyping with lower compute demands.

Comparați cu GPU-uri similare

GPUVRAM per GPUArhitecturăCalcul FP32De la / orăDetalii
RTX 508016 GBBlackwell≈ 53.4 TFLOPS—
RTX 4080S16 GBAda Lovelace≈ 50.9 TFLOPS—Detalii
RTX 408016 GBAda Lovelace≈ 48.6 TFLOPS—Detalii
RTX 5070 Ti16 GBBlackwell≈ 44.3 TFLOPS—Detalii

Întrebări frecvente

Is the RTX 5080 suitable for LLM inference and fine-tuning?

With 16 GB of VRAM and about 782 GB/s of memory bandwidth, it handles inference for compact or quantized models via vLLM or Ollama, as well as lightweight adapter fine-tuning. Full fine-tuning of large models requires a GPU with a higher memory capacity.

How does this GPU compare to larger or smaller options?

As a consumer-segment Blackwell card, the RTX 5080 offers compute capability 12.0 and about 53.4 TFLOPS at 360 W, providing more throughput than entry-level consumer cards. However, its 16 GB VRAM ceiling is more restrictive than higher-tier consumer, workstation, or datacenter GPUs designed for massive memory workloads.

What software templates and access methods are included on ONIE?

Instances include full SSH access and can be launched with pre-configured templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. The environment supports workflows targeting compute capability 12.0.

How does billing work for RTX 5080 instances?

Usage on ONIE is billed on a per-hour basis. This allows you to rent the GPU for short testing sessions or extended runs without long-term commitments.

Închiriați RTX 5080 pe oră

Creați un cont, alegeți o configurație și conectați-vă prin SSH. Facturarea se oprește când ștergeți GPU-ul.

Închiriați RTX 5080

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