Nuomokite NVIDIA RTX 2060S GPU per valandą
The NVIDIA RTX 2060S is a consumer-segment GPU built on the Turing architecture with 8 GB of VRAM and compute capability 7.5. On ONIE, it delivers about 7.5 TFLOPS of single-precision performance and about 370 GB/s of memory bandwidth inside a 175 W power envelope. You can launch instances with per-hour billing, full SSH access, and preconfigured templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
Specifikacijos
VRAM kiekvienam GPU
Architektūra
Compute capability
FP32 skaičiavimas
Atminties pralaidumas
Galios riba
Infrastruktūros teikėjo pateiktos reikšmės dabar siūlomoms mašinoms; tikrasis našumas skiriasi priklausomai nuo mašinos.
Turimos konfigūracijos
Aktualus prieinamumas ir kainos, atnaujinami nuolat. Galutinę kainą patvirtinsite prieš užsakymą.
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Kam tinka RTX 2060S
Compact Language Model Inference
Run small quantized models using Ollama or vLLM within the 8 GB VRAM capacity.
Image Generation Workflows
Execute standard diffusion pipelines in ComfyUI backed by about 370 GB/s of memory bandwidth.
Code Prototyping and Debugging
Develop and test PyTorch/CUDA scripts on a Turing GPU with compute capability 7.5 before scaling up.
Lightweight Model Training
Train small neural networks and tabular models using about 7.5 TFLOPS of single-precision compute.
Ar tai tinkamas GPU jums?
Choose the RTX 2060S for entry-level development, testing, and lightweight inference tasks that fit comfortably into 8 GB of memory. Opt for a GPU with more VRAM and higher compute if you need to fine-tune large models or run heavy production workloads, or a smaller GPU only for basic display or minimal compute tasks.
Palyginti su panašiais GPU
Dažniausiai užduodami klausimai
Is the RTX 2060S suitable for LLM inference and fine-tuning?
With 8 GB of VRAM and about 370 GB/s of memory bandwidth, the RTX 2060S can handle inference for small, quantized language models via Ollama or vLLM. Fine-tuning or running larger models requires a GPU with a higher memory capacity.
How does this Turing GPU handle image generation?
The RTX 2060S supports standard image generation workflows in ComfyUI as long as the model checkpoints and intermediate tensors stay within the 8 GB VRAM limit. Users working with larger diffusion models or high-resolution batches should select a card with more memory.
How does the RTX 2060S compare to larger GPUs?
As a consumer Turing card with compute capability 7.5 and about 7.5 TFLOPS of single-precision throughput, it is designed for lighter workloads compared to newer architectures or workstation and datacenter GPUs that offer more VRAM and higher memory bandwidth.
How do billing and instance access work on ONIE?
Instances are billed on a per-hour basis while active. You can connect directly via SSH or start immediately with ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI.
Nuomokite RTX 2060S valandomis
Sukurkite paskyrą, pasirinkite konfigūraciją ir prisijunkite per SSH. Mokėjimas nutraukiamas, kai ištrinate GPU.
Nuomoti RTX 2060S