GPU Cloud · NVIDIA · Turing

Изнајмите NVIDIA RTX 2060S GPU по сату

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.

Спецификације

VRAM по GPU-у

8 GB

Архитектура

NVIDIA Turing

Compute capability

7.5

FP32 рачунање

≈ 7.5 TFLOPS

Меморијска пропусност

≈ 370 GB/s

Ограничење снаге

175 W

Вредности које пријављује добављач инфраструктуре за тренутно наведене машине; стварне перформансе се разликују од машине до машине.

Доступне конфигурације

Актуелне залихе и цене, ажурирају се непрекидно. Коначна цена се потврђује пре наручивања.

Учитавање цена у живо…

За шта је RTX 2060S добар

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.

Да ли је то прави GPU за вас?

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.

Упоредите са сличним GPU-овима

GPUVRAM по GPU-уАрхитектураFP32 рачунањеОд / сатДетаљи
RTX 2060S8 GBTuring≈ 7.5 TFLOPS—
GTX 1070 Ti8 GBPascal≈ 7.4 TFLOPS—Детаљи
Q RTX 40008 GBTuring≈ 7.7 TFLOPS—Детаљи
RTX 20708 GBTuring≈ 7.7 TFLOPS—Детаљи

Често постављана питања

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.

Изнајмите RTX 2060S по сату

Креирајте налог, изаберите конфигурацију и повежите се преко SSH-а. Наплата престаје када обришете GPU.

Изнајмите RTX 2060S

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