Nuomokite NVIDIA RTX 3070 GPU per valandą
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.
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 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.
Ar tai tinkamas GPU jums?
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.
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Dažniausiai užduodami klausimai
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.
Nuomokite RTX 3070 valandomis
Sukurkite paskyrą, pasirinkite konfigūraciją ir prisijunkite per SSH. Mokėjimas nutraukiamas, kai ištrinate GPU.
Nuomoti RTX 3070