NVIDIA Tesla P40 · 24GB VRAM

Tensor 拖速 GPU VPS

使用专用的NVIDIA GPU硬件的加速Tensor Flow工作量。 培训模型,为预测服务,在CUDA的全力支持下建造ML输油管。

$ pip install tensorflow[and-cuda]
# 运行于 NVIDIA Tesla P40 (24GB)
准备就绪 。 _

GPU VPS上是什么?

TensorFlow 是谷歌用于建立和部署 ML 模型的开放源码机器学习框架。 GPU VPS 提供专用硬件, 用于在不共享资源的情况下加快培训和推论。

为什么在 VPS.org GPU 上TensorFlow

GPU 加速

本地CUDA支持Tensor Flow 操作,比CPU快50倍

Keras 可兼容

GPU 后端高级模型建筑的全Keras 集成。

特ensor 博板

在您自己的服务器上与 TensorBoard 一起进行监视器训练 。

TF 战备就绪

与TensorFlow在GPU上服务公司一起部署生产模型。

流行 TensorFlow 使用案例

图像分类
物体探测
自然语言处理
建议系统
时间序列预测
生产ML输油管

GPU 指定

GPU 通用 GPUNVIDIA Tesla P40
卷内24 GB GDDR5X
CUDA核心3,840
FP3212 TFLOPS
INT847 TOPS
内存 BW346 GB/s
建筑结构Pascal (GP102)
被动通过巴巴金属多氯二苯基

常问问题

What is TensorFlow on a GPU VPS?

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TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.

How do I set up TensorFlow on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for TensorFlow?

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Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.

Is TensorFlow GPU VPS billed hourly or monthly?

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GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.

Can I run other tools alongside TensorFlow?

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Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside TensorFlow.

Do I get full root on the TensorFlow GPU VPS?

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Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for TensorFlow however you need.

Which CUDA version is installed for TensorFlow?

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GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your TensorFlow workload.

Does my TensorFlow GPU VPS persist between sessions?

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Yes — your TensorFlow GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.

Where should I store data for my TensorFlow workload?

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Keep working data on the VPS SSD for fast access during TensorFlow runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.

Can I scale my TensorFlow GPU VPS later?

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Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your TensorFlow install carries over.

Are backups available for my GPU VPS?

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Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long TensorFlow training runs where you want a checkpointable server state.

Is there a money-back guarantee on the GPU VPS?

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Yes — 30-day money-back guarantee on every plan including GPU. Try TensorFlow on a GPU VPS risk-free.

准备在 GPU 上运行 TensorFlow 吗?

在几分钟内部署专用的 NVIDIA GPU 服务器。 没有预约, 没有销售电话 。