Najemite GPU NVIDIA RTX 4070 na uro
The NVIDIA RTX 4070 is a consumer-segment GPU built on the Ada Lovelace architecture, available to rent on ONIE. It offers 12 GB of VRAM, a memory bandwidth of about 440 GB/s, and single-precision compute performance of about 29.3 TFLOPS within a 200 W power envelope. Supporting CUDA compute capability 8.9, this instance suits small-scale AI inference, image generation, and code development.
Specifikacije
VRAM na GPU
Arhitektura
Računska zmogljivost
Računska zmogljivost FP32
Pasovna širina pomnilnika
Omejitev moči
Vrednosti, ki jih za trenutno navedene stroje sporoča ponudnik infrastrukture; dejanska zmogljivost se razlikuje glede na stroj.
Razpoložljive konfiguracije
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Za kaj je RTX 4070 primeren
Quantized LLM Inference
Run compact or quantized language models within the 12 GB VRAM buffer using ready templates like Ollama or vLLM.
Diffusion Image Generation
Generate images and test node workflows in ComfyUI leveraging the Ada Lovelace architecture and about 29.3 TFLOPS of compute.
PyTorch Prototyping and Debugging
Write, test, and debug deep learning scripts in a PyTorch/CUDA environment with compute capability 8.9 before scaling up.
Lightweight Model Fine-Tuning
Execute parameter-efficient fine-tuning on small datasets that fit comfortably inside 12 GB of memory at about 440 GB/s bandwidth.
Ali je to pravi GPU za vas?
The RTX 4070 is a practical choice for developers who need modern Ada Lovelace architecture features and 12 GB of VRAM for prototyping or moderate inference workloads. Select a GPU with more VRAM if your models or batch sizes exceed 12 GB, or opt for an older or smaller consumer GPU if you only run minimal testing scripts.
Primerjajte s podobnimi GPU-ji
| GPU | VRAM na GPU | Arhitektura | Računska zmogljivost FP32 | Od / uro | Podrobnosti |
|---|---|---|---|---|---|
| RTX 4070 | 12 GB | Ada Lovelace | ≈ 29.3 TFLOPS | — | |
| RTX 3080 | 10 GB | Ampere | ≈ 29.5 TFLOPS | — | Podrobnosti |
| RTX 3080 Ti | 12 GB | Ampere | ≈ 35.1 TFLOPS | — | Podrobnosti |
| RTX 4070S | 12 GB | Ada Lovelace | ≈ 35.8 TFLOPS | — | Podrobnosti |
Pogosta vprašanja
Is the RTX 4070 suitable for LLM inference?
Yes, the 12 GB of VRAM and about 440 GB/s of memory bandwidth allow it to run small or quantized language models efficiently. You can deploy these workloads quickly on ONIE using pre-configured Ollama or vLLM templates.
When should I choose a larger GPU over the RTX 4070?
If your workload involves full fine-tuning, large batch sizes, or unquantized models that exceed the 12 GB VRAM limit, you should select a higher-tier consumer or workstation GPU. The RTX 4070 is intended for lightweight training and moderate inference tasks.
What software environments are available for this GPU?
ONIE provides ready-to-use templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI, all compatible with CUDA compute capability 8.9. You also get full SSH access to install custom libraries and manage your files directly.
How does billing work for RTX 4070 instances?
Instances on ONIE use per-hour billing, so you only pay for the time your RTX 4070 instance is active.
Najamite RTX 4070 po uri
Ustvarite račun, izberite konfiguracijo in se povežite prek SSH. Obračun se ustavi, ko izbrišete GPU.
Najamite RTX 4070