Наемете NVIDIA RTX 3070 GPU на почасова база
The NVIDIA RTX 3070 is a consumer-segment Ampere architecture GPU equipped with 8 GB of VRAM and a 220 W TDP. On ONIE, this card provides about 19.8 TFLOPS of single-precision compute and about 386 GB/s of memory bandwidth. With compute capability 8.6, it serves as a practical option for development, prototyping, and lightweight inference tasks.
Спецификации
VRAM на GPU
Архитектура
Изчислителна способност
FP32 изчисления
Пропускателна способност на паметта
Лимит на мощността
Стойностите са предоставени от доставчика на инфраструктурата за машините, които са в момента в списъка; реалната производителност варира в зависимост от машината.
Налични конфигурации
Наличността и цените са в реално време и се обновяват непрекъснато. Крайната цена се потвърждава, преди да поръчате.
Зареждане на цените в реално време…
За какво е подходящ RTX 3070
Lightweight LLM Inference
Run quantized small language models using ready Ollama or vLLM templates within the 8 GB VRAM envelope.
Image Generation Workflows
Generate standard-resolution images and test node workflows using the pre-configured ComfyUI template.
PyTorch Code Prototyping
Develop, debug, and verify machine learning scripts on Ampere hardware with compute capability 8.6 before scaling up.
Batch Data Processing
Utilize about 19.8 TFLOPS of single-precision performance and about 386 GB/s memory bandwidth for GPU-accelerated data pipelines.
Подходящ ли е този GPU за вас?
Choose the RTX 3070 for code testing, lightweight inference, and small-scale image generation that fits comfortably inside 8 GB of memory. Select a GPU with more VRAM for fine-tuning or large model weights, or step down to an entry-level card if your workload requires minimal compute.
Сравнете с подобни GPU
| GPU | VRAM на GPU | Архитектура | FP32 изчисления | От / час | Подробности |
|---|---|---|---|---|---|
| RTX 3070 | 8 GB | Ampere | ≈ 19.8 TFLOPS | — | |
| RTX 3060 Ti | 8 GB | Ampere | ≈ 15.7 TFLOPS | — | Подробности |
| RTX A4000 | 16 GB | Ampere | ≈ 20.6 TFLOPS | — | Подробности |
| RTX 2080 Ti | 11 GB | Turing | ≈ 14.6 TFLOPS | — | Подробности |
Често задавани въпроси
Is the RTX 3070 suitable for LLM inference and fine-tuning?
With 8 GB of VRAM, the RTX 3070 can handle inference for small, quantized language models using templates like Ollama or vLLM. For full fine-tuning or running larger models, you should choose a GPU with a larger memory capacity.
How do I connect to my RTX 3070 instance on ONIE?
You can connect directly via SSH access for command-line workflows or launch pre-configured templates including PyTorch/CUDA, ComfyUI, Ollama, and vLLM. Billing is calculated on a per-hour basis while your instance is active.
What CUDA features does the RTX 3070 support?
As an Ampere generation consumer GPU, the RTX 3070 supports compute capability 8.6. This allows it to run modern PyTorch/CUDA workloads that fit within its 8 GB memory limit.
How does the RTX 3070 compare to higher-tier Ampere GPUs?
The RTX 3070 delivers about 19.8 TFLOPS of single-precision compute and about 386 GB/s of memory bandwidth at a 220 W TDP. Stepping up to higher-tier Ampere consumer or workstation GPUs provides increased VRAM capacity and higher memory bandwidth for heavier workloads.
Наемете RTX 3070 на час
Създайте акаунт, изберете конфигурация и се свържете през SSH. Таксуването спира, когато изтриете GPU-то.
Наемете RTX 3070