Najemite GPU NVIDIA GTX TITAN X na uro
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 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 GTX TITAN X primeren
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.
Ali je 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.
Primerjajte s podobnimi GPU-ji
| GPU | VRAM na GPU | Arhitektura | Računska zmogljivost FP32 | Od / uro | Podrobnosti |
|---|---|---|---|---|---|
| GTX TITAN X | 12 GB | Maxwell | ≈ 6.8 TFLOPS | — | |
| RTX 2060 | 12 GB | Turing | ≈ 6.5 TFLOPS | — | Podrobnosti |
| GTX 1070 Ti | 8 GB | Pascal | ≈ 7.4 TFLOPS | — | Podrobnosti |
| RTX 2060S | 8 GB | Turing | ≈ 7.5 TFLOPS | — | Podrobnosti |
Pogosta vprašanja
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.
Najamite GTX TITAN X po uri
Ustvarite račun, izberite konfiguracijo in se povežite prek SSH. Obračun se ustavi, ko izbrišete GPU.
Najamite GTX TITAN X