Prenájom GPU NVIDIA RTX 3080 po hodinách
The NVIDIA RTX 3080 is an Ampere-architecture consumer GPU equipped with 10 GB of VRAM. It delivers about 29.5 TFLOPS of standard floating-point compute and a memory bandwidth of about 656 GB/s. On ONIE, you can deploy this GPU with per-hour billing, SSH access, and ready templates.
Špecifikácie
VRAM na jedno GPU
Architektúra
Výpočtová schopnosť
Výpočtový výkon FP32
Šírka pásma pamäte
Limit príkonu
Hodnoty uvádza poskytovateľ infraštruktúry pre aktuálne ponúkané stroje; skutočný výkon sa môže podľa stroja líšiť.
Dostupné konfigurácie
Aktuálna dostupnosť a ceny, priebežne aktualizované. Konečná cena sa potvrdí pred objednávkou.
Načítavajú sa aktuálne ceny…
Na čo sa RTX 3080 hodí
Compact LLM Inference
Run quantized language models that fit within 10 GB of VRAM using pre-configured Ollama or vLLM templates.
Image Generation Workflows
Execute diffusion pipelines in ComfyUI leveraging about 656 GB/s of memory bandwidth for steady image output.
PyTorch Model Prototyping
Develop and test deep learning code on an Ampere card with compute capability 8.6 before scaling up.
CUDA Compute Tasks
Accelerate custom workloads that utilize about 29.5 TFLOPS of standard floating-point performance.
Je to pre vás správne GPU?
Choose the RTX 3080 for prototyping, image generation, and small-scale inference where 10 GB of VRAM and strong Ampere compute are sufficient. Opt for a GPU with more memory if your models or batch sizes exceed 10 GB, or select a lower-spec consumer card for lightweight scripts that do not require about 29.5 TFLOPS.
Porovnajte s podobnými GPU
| GPU | VRAM na jedno GPU | Architektúra | Výpočtový výkon FP32 | Od / hodina | Podrobnosti |
|---|---|---|---|---|---|
| RTX 3080 | 10 GB | Ampere | ≈ 29.5 TFLOPS | — | |
| RTX 4070 | 12 GB | Ada Lovelace | ≈ 29.3 TFLOPS | — | Podrobnosti |
| RTX 3080 Ti | 12 GB | Ampere | ≈ 35.1 TFLOPS | — | Podrobnosti |
| RTX 4070S | 12 GB | Ada Lovelace | ≈ 35.8 TFLOPS | — | Podrobnosti |
Často kladené otázky
Is the RTX 3080 suitable for LLM inference and image generation?
Yes, its 10 GB of VRAM and about 656 GB/s of memory bandwidth handle standard image generation in ComfyUI and quantized language models via Ollama or vLLM. Larger unquantized models will require a GPU with a higher memory capacity.
What software templates are available for the RTX 3080 on ONIE?
You can launch instances with ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. The card supports compute capability 8.6 for broad compatibility with modern machine learning frameworks.
When should I step up from the RTX 3080 to a larger GPU?
The RTX 3080 provides strong consumer-class compute at about 29.5 TFLOPS within a 380 W power envelope, but it is limited to 10 GB of VRAM. If your training batches or model weights cause out-of-memory errors, a workstation or datacenter GPU with a larger memory buffer is the appropriate choice.
How do billing and access work on ONIE?
Instances are billed on a per-hour basis while active. You receive full SSH access to manage your environment alongside any web interfaces provided by your chosen template.
Prenajmite si RTX 3080 na hodiny
Vytvorte si účet, vyberte konfiguráciu a pripojte sa cez SSH. Fakturácia sa zastaví, keď GPU vymažete.
Prenajať RTX 3080