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
INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT847 TOPS
内存 BW346 GB/s
建筑结构结构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 。

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