GPU Cloud · NVIDIA · Turing

Изнајмите NVIDIA RTX 2060 GPU по сату

The NVIDIA RTX 2060 on ONIE is a Turing-architecture consumer GPU featuring 12 GB of VRAM and a 130 W TDP. It delivers about 6.5 TFLOPS of single-precision compute and about 268 GB/s of memory bandwidth with CUDA compute capability 7.5. Instances include SSH access, per-hour billing, and preconfigured templates for PyTorch/CUDA, ComfyUI, Ollama, and vLLM.

Спецификације

VRAM по GPU-у

12 GB

Архитектура

NVIDIA Turing

Compute capability

7.5

FP32 рачунање

≈ 6.5 TFLOPS

Меморијска пропусност

≈ 268 GB/s

Ограничење снаге

130 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 2060 добар

Entry-Level Image Generation

Run ComfyUI workflows and standard diffusion models that fit comfortably within 12 GB of VRAM.

Compact Language Model Inference

Deploy quantized or smaller language models using Ollama or vLLM for lightweight text generation tasks.

PyTorch Prototyping and Debugging

Write, test, and debug CUDA code on a Turing architecture card before scaling up to larger instances.

Small-Scale Model Training

Train modest neural networks and machine learning pipelines using the PyTorch/CUDA template.

Да ли је то прави GPU за вас?

Choose the 12 GB RTX 2060 when your workload needs more memory than entry-level consumer cards offer, without requiring the higher compute throughput of newer architectures. Upgrade to a newer generation or workstation GPU for heavy training, or pick a smaller GPU if your task requires minimal VRAM.

Упоредите са сличним GPU-овима

GPUVRAM по GPU-уАрхитектураFP32 рачунањеОд / сатДетаљи
RTX 206012 GBTuring≈ 6.5 TFLOPS—
GTX TITAN X12 GBMaxwell≈ 6.8 TFLOPS—Детаљи
GTX 1070 Ti8 GBPascal≈ 7.4 TFLOPS—Детаљи
RTX 2060S8 GBTuring≈ 7.5 TFLOPS—Детаљи

Често постављана питања

Is the RTX 2060 suitable for LLM inference?

With 12 GB of VRAM and about 268 GB/s of memory bandwidth, it can handle compact and quantized language models via Ollama or vLLM. Larger models or high-throughput serving will require a GPU with more memory and higher bandwidth.

What software compatibility does the Turing architecture offer?

The RTX 2060 supports CUDA compute capability 7.5, which runs standard frameworks included in the PyTorch/CUDA template. Note that it lacks hardware support for certain newer data types introduced in later architectures.

How does this 12 GB RTX 2060 compare to other consumer GPUs?

The 12 GB memory capacity allows it to hold larger models and batch sizes than lower-memory consumer variants, though its about 6.5 TFLOPS of compute is more modest than newer-generation cards.

How do billing and instance access work on ONIE?

Instances are billed on a per-hour basis. You can connect directly via SSH or launch right into pre-configured templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI.

Изнајмите RTX 2060 по сату

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

Изнајмите RTX 2060

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