Īrējiet NVIDIA Tesla V100 GPU pa stundām
The NVIDIA Tesla V100 is a Volta-architecture datacenter GPU equipped with 16 GB of high-bandwidth VRAM and a 300 W thermal design power. It delivers about 12.5 TFLOPS of single-precision compute and about 780 GB/s of memory bandwidth, making it a dependable option for memory-intensive scientific computing and deep learning tasks. On ONIE, you can deploy the Tesla V100 with per-hour billing, full SSH access, and pre-configured templates.
Specifikācijas
VRAM katram GPU
Arhitektūra
Skaitļošanas spēja
FP32 skaitļošana
Atmiņas joslas platums
Jaudas ierobežojums
Vērtības, ko par pašlaik piedāvātajiem serveriem norādījis infrastruktūras nodrošinātājs; reālā veiktspēja dažādos serveros var atšķirties.
Pieejamās konfigurācijas
Aktuālie krājumi un cenas, kas tiek atjaunotas nepārtraukti. Galīgā cena tiek apstiprināta pirms pasūtīšanas.
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Kam ir piemērots Tesla V100
Compact LLM Inference
Serve quantized or smaller language models using Ollama or vLLM templates while taking advantage of about 780 GB/s of memory bandwidth.
Deep Learning Prototyping
Train and validate neural network architectures in PyTorch with 16 GB of VRAM and compute capability 7.0.
Image Generation Workflows
Run diffusion pipelines and custom generation graphs through pre-installed ComfyUI templates.
Scientific Simulation and Compute
Execute bandwidth-bound datacenter workloads that benefit from Volta architecture and about 12.5 TFLOPS of single-precision performance.
Vai tas ir piemērots GPU Jums?
The 16 GB Tesla V100 suits researchers and developers who need high memory bandwidth for small-to-medium models and scientific workloads without paying for newer datacenter hardware. Choose a smaller consumer GPU for basic development with lower memory needs, or step up to a newer generation GPU with larger VRAM if your models exceed 16 GB or require newer architectural features beyond compute capability 7.0.
Salīdzināt ar līdzīgiem GPU
Biežāk uzdotie jautājumi
Is the 16 GB Tesla V100 suitable for LLM inference and fine-tuning?
The 16 GB of VRAM and about 780 GB/s of memory bandwidth make the Tesla V100 suitable for inference on smaller or quantized language models and parameter-efficient fine-tuning. For larger models that do not fit into 16 GB of memory, you should select a GPU with a higher VRAM capacity.
What software templates and connection methods are available on ONIE?
Every Tesla V100 instance includes direct SSH access for custom configuration and command-line workflows. You can also launch ready templates including PyTorch/CUDA, vLLM, Ollama, and ComfyUI to start working immediately.
How does the Volta architecture affect framework compatibility?
The Tesla V100 supports CUDA compute capability 7.0, which is compatible with standard deep learning frameworks like PyTorch. However, workloads that explicitly require features introduced in newer compute capabilities will need a more recent GPU architecture.
How does billing work for renting the Tesla V100?
ONIE uses straightforward per-hour billing for all Tesla V100 rentals. You only pay for the time your instance is active, allowing you to run experiments or batch jobs and terminate the server when finished.
Nomājiet Tesla V100 pa stundām
Izveidojiet kontu, izvēlieties konfigurāciju un pieslēdzieties caur SSH. Norēķini tiek pārtraukti, kad dzēšat GPU.
Nomāt Tesla V100