Najemite GPU NVIDIA GTX 1080 na uro
The NVIDIA GTX 1080 is a consumer-segment Pascal GPU equipped with 8 GB of VRAM and a 130 W TDP. On ONIE, it delivers about 7.8 TFLOPS of single-precision compute and about 227 GB/s of memory bandwidth. With compute capability 6.1, it serves entry-level CUDA development, lightweight inference, and basic rendering tasks.
Specifikacije
VRAM na GPU
Arhitektura
Računska zmogljivost
Računska zmogljivost FP32
Pasovna širina pomnilnika
Omejitev moči
Vrednosti, ki jih za trenutno navedene stroje sporoča ponudnik infrastrukture; dejanska zmogljivost se razlikuje glede na stroj.
Razpoložljive konfiguracije
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Za kaj je GTX 1080 primeren
Entry-Level CUDA Development
Write, compile, and debug CUDA code targeting Pascal compute capability 6.1 via SSH access.
Small Model Inference
Run compact neural networks and quantized language models that fit comfortably within 8 GB of VRAM using Ollama or PyTorch templates.
Basic Image Generation
Execute standard image synthesis workflows in ComfyUI where 8 GB of memory and about 227 GB/s bandwidth are sufficient.
Classical Machine Learning
Train and evaluate tabular models or small convolutional networks utilizing about 7.8 TFLOPS of single-precision performance.
Ali je to pravi GPU za vas?
Pick the GTX 1080 for prototyping, learning, and lightweight workloads that fit inside 8 GB of VRAM and do not require modern tensor cores. Choose a newer or larger GPU if your workload requires more than 8 GB of memory, native mixed-precision acceleration, or higher memory bandwidth.
Primerjajte s podobnimi GPU-ji
| GPU | VRAM na GPU | Arhitektura | Računska zmogljivost FP32 | Od / uro | Podrobnosti |
|---|---|---|---|---|---|
| GTX 1080 | 8 GB | Pascal | ≈ 7.8 TFLOPS | — | |
| Q RTX 4000 | 8 GB | Turing | ≈ 7.7 TFLOPS | — | Podrobnosti |
| RTX 2070 | 8 GB | Turing | ≈ 7.7 TFLOPS | — | Podrobnosti |
| RTX 2060S | 8 GB | Turing | ≈ 7.5 TFLOPS | — | Podrobnosti |
Pogosta vprašanja
Is the GTX 1080 suitable for LLM inference or fine-tuning?
With 8 GB of VRAM and Pascal architecture, the GTX 1080 can run inference on small, heavily quantized models using templates like Ollama. For larger language models or fine-tuning tasks, a GPU with more VRAM and a newer compute capability is recommended.
What software templates and access methods are available on ONIE?
You can deploy the GTX 1080 with pre-configured templates including PyTorch/CUDA, ComfyUI, Ollama, and vLLM. Full SSH access is provided so you can customize your environment and manage files directly.
How does the Pascal architecture affect modern deep learning frameworks?
The GTX 1080 supports CUDA compute capability 6.1, which runs standard single-precision operations at about 7.8 TFLOPS. Because it lacks the specialized matrix cores found in newer architectures, frameworks relying on hardware-accelerated lower-precision formats will run slower or require fallback modes.
How does billing work for renting a GTX 1080?
Instances on ONIE use per-hour billing, so you only pay for the time your GTX 1080 instance is active.
Najamite GTX 1080 po uri
Ustvarite račun, izberite konfiguracijo in se povežite prek SSH. Obračun se ustavi, ko izbrišete GPU.
Najamite GTX 1080