Iznajmite NVIDIA GTX TITAN X GPU po satu
The NVIDIA GTX TITAN X is a Maxwell-architecture consumer GPU available for rental on ONIE. It offers 12 GB of VRAM, about 6.8 TFLOPS of single-precision compute, and about 239 GB/s of memory bandwidth within a 150 W power envelope. Supporting CUDA compute capability 5.2, it handles legacy GPU tasks, development, and entry-level deep learning workflows.
Specifikacije
VRAM po GPU-u
Arhitektura
Računalna sposobnost
FP32 računanje
Propusnost memorije
Ograničenje snage
Vrijednosti koje je navela infrastrukturna platforma za trenutno navedene strojeve; stvarne performanse razlikuju se ovisno o stroju.
Dostupne konfiguracije
Zalihe i cijene u stvarnom vremenu, neprekidno ažurirane. Konačnu cijenu potvrđujemo prije narudžbe.
Učitavanje cijena u stvarnom vremenu…
Za što je GTX TITAN X pogodan
Legacy CUDA Development
Test and maintain software targeting the Maxwell architecture and CUDA compute capability 5.2.
Entry-Level Deep Learning
Run basic training and prototyping workflows in PyTorch that fit within 12 GB of VRAM.
Lightweight Model Inference
Deploy small language or vision models using templates like Ollama where moderate memory bandwidth of about 239 GB/s is sufficient.
Standard Image Generation
Execute basic diffusion pipelines in ComfyUI that require up to 12 GB of video memory without demanding modern tensor cores.
Je li to pravi GPU za vas?
Choose the GTX TITAN X when you need 12 GB of VRAM for development, legacy software compatibility, or light inference without paying for newer architectures. Select a smaller GPU if your workload uses minimal memory, or upgrade to a newer, larger GPU if you need modern compute capabilities and higher memory bandwidth for large-scale training.
Usporedite sa sličnim GPU-ovima
| GPU | VRAM po GPU-u | Arhitektura | FP32 računanje | Od / sat | Pojedinosti |
|---|---|---|---|---|---|
| GTX TITAN X | 12 GB | Maxwell | ≈ 6.8 TFLOPS | — | |
| RTX 2060 | 12 GB | Turing | ≈ 6.5 TFLOPS | — | Pojedinosti |
| GTX 1070 Ti | 8 GB | Pascal | ≈ 7.4 TFLOPS | — | Pojedinosti |
| RTX 2060S | 8 GB | Turing | ≈ 7.5 TFLOPS | — | Pojedinosti |
Često postavljana pitanja
Is the GTX TITAN X suitable for LLM inference and image generation?
With 12 GB of VRAM, it can hold small models for inference in Ollama or basic pipelines in ComfyUI. However, because it uses the older Maxwell architecture with compute capability 5.2 and about 6.8 TFLOPS of single-precision performance, generation will be slower than on newer GPUs.
Does this GPU support modern frameworks like PyTorch and vLLM?
ONIE provides ready templates for PyTorch/CUDA, vLLM, Ollama, and ComfyUI. Because the GTX TITAN X is a Maxwell-generation card with compute capability 5.2, some newer software features or quantization methods in tools like vLLM may require a GPU with a newer architecture.
How does the GTX TITAN X compare to smaller or larger GPUs?
Its 12 GB of VRAM provides more room for data and weights than smaller entry-level consumer cards. Compared to newer workstation or datacenter GPUs, its about 239 GB/s of memory bandwidth and Maxwell architecture make it better suited for light tasks rather than heavy production workloads.
How do billing and access work on ONIE?
Rentals are billed on a per-hour basis while your instance is active. You can connect directly to your environment via SSH access or launch pre-configured templates straight from the dashboard.
Iznajmite GTX TITAN X po satu
Stvorite račun, odaberite konfiguraciju i povežite se putem SSH-a. Naplata prestaje kada izbrišete GPU.
Iznajmi GTX TITAN X