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GPU AI 托管





RTX 4090 · RTX 5090 · H100 SXM5 · CUDA 12


# 匿名离岸 GPU AI 托管 免KYC



NVIDIA RTX 4090、RTX 5090 及 H100 SXM5 GPU 服务器，适用于 AI 训练、推理、图像与视频生成。预装 CUDA 12 与 cuDNN，以及 PyTorch / ComfyUI / Ollama 镜像预设，ssh 直连即用。H100 层级搭载 Threadripper Pro 宿主机，提供完整 PCIe Gen 5 通道数。在 4 个离岸司法管辖区可用，无 KYC，支持含 Monero 在内的 20 种加密货币支付。


[查看 GPU 方案](#plans)
[独立服务器](https://servprivate.com/zh/dedicated)






#### 每台 GPU 服务器均含




- NVIDIA 硬件，完整直通

- CUDA 12 + cuDNN 预装

- Threadripper / Ryzen 9 宿主机

- NVMe SSD & DDR5

- 60 秒部署

- 20 cryptos accepted incl. Monero






无需KYC
仅限加密货币
CUDA 12
纯净 IP
完整Root权限
Monero accepted


全部 GPU 方案


## 按地区选择 GPU 方案



所有司法管辖区使用相同 NVIDIA 硬件，所有方案均提供无限带宽。定价因地区而异——Iceland 碳排放最低，Moldova 价格最优。






### 冰岛
言论自由港


| 方案 | GPU | VRAM | CPU | 内存 | NVMe | 带宽 | 价格 | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| IS-S | 1× NVIDIA RTX 4090 | 24 GB GDDR6X | 12 vCPU | 64 GB DDR5 | 1 TB NVMe | 无限 | $146.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=IS-S&location=iceland) |
| IS-M 热门 | 1× NVIDIA RTX 5090 | 32 GB GDDR7 | 16 vCPU | 96 GB DDR5 | 1.5 TB NVMe | 无限 | $234.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=IS-M&location=iceland) |
| IS-L | 1× NVIDIA H100 SXM5 | 80 GB HBM3 | 24 vCPU | 192 GB DDR5 | 2 TB NVMe | 无限 | $906.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=IS-L&location=iceland) |
| IS-XL | 2× NVIDIA H100 SXM5 | 160 GB HBM3 | 32 vCPU | 384 GB DDR5 | 4 TB NVMe | 无限 | $1714.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=IS-XL&location=iceland) |





### 摩尔多瓦
经济型离岸


| 方案 | GPU | VRAM | CPU | 内存 | NVMe | 带宽 | 价格 | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MD-S | 1× NVIDIA RTX 4090 | 24 GB GDDR6X | 12 vCPU | 64 GB DDR5 | 1 TB NVMe | 无限 | $122.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=MD-S&location=moldova) |
| MD-M 热门 | 1× NVIDIA RTX 5090 | 32 GB GDDR7 | 16 vCPU | 96 GB DDR5 | 1.5 TB NVMe | 无限 | $195.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=MD-M&location=moldova) |
| MD-L | 1× NVIDIA H100 SXM5 | 80 GB HBM3 | 24 vCPU | 192 GB DDR5 | 2 TB NVMe | 无限 | $832.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=MD-L&location=moldova) |
| MD-XL | 2× NVIDIA H100 SXM5 | 160 GB HBM3 | 32 vCPU | 384 GB DDR5 | 4 TB NVMe | 无限 | $1567.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=MD-XL&location=moldova) |





### 罗马尼亚
反数据留存


| 方案 | GPU | VRAM | CPU | 内存 | NVMe | 带宽 | 价格 | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| RO-S | 1× NVIDIA RTX 4090 | 24 GB GDDR6X | 12 vCPU | 64 GB DDR5 | 1 TB NVMe | 无限 | $132.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=RO-S&location=romania) |
| RO-M 热门 | 1× NVIDIA RTX 5090 | 32 GB GDDR7 | 16 vCPU | 96 GB DDR5 | 1.5 TB NVMe | 无限 | $210.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=RO-M&location=romania) |
| RO-L | 1× NVIDIA H100 SXM5 | 80 GB HBM3 | 24 vCPU | 192 GB DDR5 | 2 TB NVMe | 无限 | $857.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=RO-L&location=romania) |
| RO-XL | 2× NVIDIA H100 SXM5 | 160 GB HBM3 | 32 vCPU | 384 GB DDR5 | 4 TB NVMe | 无限 | $1616.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=RO-XL&location=romania) |





### 荷兰
最佳对等互联


| 方案 | GPU | VRAM | CPU | 内存 | NVMe | 带宽 | 价格 | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| NL-S | 1× NVIDIA RTX 4090 | 24 GB GDDR6X | 12 vCPU | 64 GB DDR5 | 1 TB NVMe | 无限 | $136.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=NL-S&location=netherlands) |
| NL-M 热门 | 1× NVIDIA RTX 5090 | 32 GB GDDR7 | 16 vCPU | 96 GB DDR5 | 1.5 TB NVMe | 无限 | $220.00/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=NL-M&location=netherlands) |
| NL-L | 1× NVIDIA H100 SXM5 | 80 GB HBM3 | 24 vCPU | 192 GB DDR5 | 2 TB NVMe | 无限 | $881.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=NL-L&location=netherlands) |
| NL-XL | 2× NVIDIA H100 SXM5 | 160 GB HBM3 | 32 vCPU | 384 GB DDR5 | 4 TB NVMe | 无限 | $1665.50/mo | [订单](https://servprivate.com/zh/order?type=gpu&plan=NL-XL&location=netherlands) |





GPU 托管在上线时提供 4 个司法管辖区（Iceland、Netherlands、Romania、Moldova）。Russia 因 NVIDIA 出口制裁被排除；Switzerland 和 Panama 目前仅提供 Linux 方案。 



## 每台 GPU 服务器标配




### CUDA 12

预装 CUDA 12.4/12.6 + cuDNN。启动后 ssh 进入，运行 nvidia-smi。



### 60 秒部署

从付款到 nvidia-smi 输出，60 秒内完成。



### NVMe SSD

最高 4 TB NVMe SSD，搭配 DDR5 内存，实现快速数据集 I/O。



### SSH + Jupyter

完全 root SSH，以及预绑定在 8888 端口、使用令牌认证的 JupyterLab。



用例

## What GPU AI Hosting is Used For




### LLM 微调与推理

在 H100 上使用 LoRA / QLoRA / 全量微调对 Llama、Mistral、Qwen、DeepSeek 进行微调。或使用 vLLM / TGI / Ollama 进行自托管推理，用于生产模型服务。



### 图像生成

使用 ComfyUI 或 Forge 运行 Stable Diffusion、FLUX.1、SDXL。训练自己的 LoRA，大规模批量生成，或自托管推理端点。



### AI 视频生成

OpenSora、CogVideoX、Wan-2.1、AnimateDiff。视频生成需要充足 VRAM — 从 RTX 5090（32 GB）或 H100（80 GB）起步。



### 生产推理

在您自己的 API 后端部署微调模型。成本可预测，无按 token 计费，数据不离开您的司法管辖区。含 JupyterLab + FastAPI。



一键部署


## 预装 AI 模板



下单时勾选任意模板，GPU 服务器启动时即完成安装、配置并通过 systemd 启动。在下方添加预下载模型，跳过 HuggingFace 30-60 分钟的下载等待。







LLM 推理


### vLLM (OpenAI-compatible)





Production-grade LLM serving with continuous batching and paged attention. Exposes an /v1/completions endpoint compatible with the OpenAI SDK.


LLMOpenAI APIproduction 16 GB+






LLM 推理


### Ollama + Open WebUI





Self-hosted ChatGPT-style web UI. Pulls Ollama-native quantized weights; easiest path to "talk to my LLM in a browser".


LLMchat UIbeginner 8 GB+






LLM 推理


### text-generation-webui (Oobabooga)





Gradio UI with broad backend support — Transformers, ExLlamaV2, llama.cpp, AWQ, GPTQ. Power-user choice for benchmarking quantizations.


LLMmulti-backendpower user 16 GB+






LLM 推理


### HuggingFace TGI





HuggingFace Text Generation Inference — production server with token streaming, tensor parallelism, paged attention.


LLMproductionHuggingFace 24 GB+






微调


### Axolotl (LLM finetuning)





YAML-config driven finetuning. Supports LoRA, QLoRA, full FT, DPO, ORPO. Pre-cloned to /opt/axolotl with starter configs for Llama / Qwen / Mistral.


finetuneLoRAQLoRA 24 GB+






微调


### Unsloth (2× faster finetune)





2× faster + 70% less VRAM finetuning via custom Triton kernels. Ideal for budget runs on RTX 4090. Pre-installed in /opt/unsloth.


finetunefastlow VRAM 16 GB+






微调


### LLaMA-Factory





WebUI-driven finetuning platform. SFT / RLHF / DPO / KTO. Good entry point for non-coders who want to finetune on a UI.


finetuneGUI 24 GB+






图像生成


### ComfyUI + FLUX.1





Node-graph image-gen interface, ships with FLUX.1-schnell + Kontext workflows. Power-user image generation pipeline.


imageFLUXworkflow 24 GB+






图像生成


### Automatic1111 + SD 3.5





The mainstream Stable Diffusion WebUI. Stable Diffusion 3.5 + extensions ecosystem. Familiar UI for users coming from civitai.


imageSD 3.5 16 GB+






图像生成


### Forge (faster A1111)





A1111 fork optimized for FLUX, faster sampling, lower VRAM. Drop-in replacement for users coming from Auto1111.


imageFLUXfast 16 GB+






图像生成


### Kohya SS (LoRA training)





GUI for training Stable Diffusion / FLUX LoRA, DreamBooth, textual inversion. Trains a custom-style LoRA on RTX 4090 in 30-90 min.


LoRA trainingimageGUI 16 GB+






AI 视频


### ComfyUI + Wan 2.2 / HunyuanVideo





ComfyUI with video-gen workflows preloaded — Wan 2.2 T2V, HunyuanVideo, LTX-Video. Needs 40+ GB VRAM for usable speed at 720p.


videoWan 2.2HunyuanVideo 40 GB+






AI 视频


### ComfyUI Video Lite (CogVideoX / LTX)





Lightweight video workflows — CogVideoX-5B, Wan 2.1 1.3B, LTX-Video. Runs on a single RTX 4090.


videoCogVideoXlow VRAM 16 GB+






音频


### Whisper Large v3 Turbo server





OpenAI Whisper Large v3 Turbo with faster-whisper backend behind a /transcribe HTTP API. 8× faster than v3, 99 langs, real-time on any GPU.


audiospeech-to-textAPI 6 GB+






音频


### TTS server (Kokoro + CSM-1B)





Multi-model TTS endpoint serving Kokoro 82M (54 voices, 8 langs) and Sesame CSM-1B (conversational with context). REST + WebSocket streaming.


audiotext-to-speechAPI 6 GB+






Notebooks & 开发


### JupyterLab + PyTorch baseline





Always installed. PyTorch 2.5 + CUDA 12.4 + Transformers + diffusers + accelerate + bitsandbytes + xformers + flash-attn. The universal AI dev baseline.


notebookbaselinealways-on 0 GB+






Notebooks & 开发


### code-server (VSCode in browser)





VSCode running in your browser, full Python/IPython/extensions. For users who prefer IDE workflow over notebooks.


IDEVSCodedev 0 GB+





在同一 GPU 上组合多个技术栈——部署脚本自动解决依赖冲突并分配不冲突的端口。

跳过下载


## 预下载开放权重模型



下单时勾选所需模型，登录前即已缓存至 /root/.cache/huggingface。🔒 受限模型（Llama、Mistral、Gemma、FLUX-dev、SD 3.5）需要您的 HuggingFace Token（下单时一并填写）。



| 模型 | HuggingFace | 大小 | 最低 VRAM | 最低 GPU 档位 | 类型 |
| --- | --- | --- | --- | --- | --- |
| **Llama 3.3 70B Instruct** 🔒 受限 | meta-llama/Llama-3.3-70B-Instruct | 140 GB | 160 GB | **GPU-L** | LLM |
| **Qwen3 32B** | Qwen/Qwen3-32B | 64 GB | 80 GB | **GPU-L** | LLM |
| **Qwen3 14B** | Qwen/Qwen3-14B | 28 GB | 32 GB | **GPU-S** | LLM |
| **Qwen3 8B** | Qwen/Qwen3-8B | 16 GB | 20 GB | **GPU-S** | LLM |
| **DeepSeek-R1 Distill Qwen 32B** | deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | 64 GB | 80 GB | **GPU-S** | LLM |
| **DeepSeek-R1 Distill Llama 70B** | deepseek-ai/DeepSeek-R1-Distill-Llama-70B | 140 GB | 160 GB | **GPU-S** | LLM |
| **Mistral Small 3.2 24B (multimodal)** | mistralai/Mistral-Small-3.2-24B-Instruct-2506 | 48 GB | 60 GB | **GPU-S** | LLM |
| **Gemma 3 27B (multimodal)** 🔒 受限 | google/gemma-3-27b-it | 54 GB | 64 GB | **GPU-L** | LLM |
| **Gemma 3 12B (multimodal)** 🔒 受限 | google/gemma-3-12b-it | 24 GB | 28 GB | **GPU-S** | LLM |
| **Phi-4 (14B)** | microsoft/phi-4 | 28 GB | 32 GB | **GPU-S** | LLM |
| **Phi-4 Mini Instruct (3.8B)** | microsoft/Phi-4-mini-instruct | 8 GB | 10 GB | **GPU-S** | LLM |
| **FLUX.1 [dev]** 🔒 受限 | black-forest-labs/FLUX.1-dev | 24 GB | 24 GB | **GPU-S** | 图像 |
| **FLUX.1 [schnell]** | black-forest-labs/FLUX.1-schnell | 24 GB | 24 GB | **GPU-S** | 图像 |
| **FLUX.1 Kontext [dev] (image editing)** 🔒 受限 | black-forest-labs/FLUX.1-Kontext-dev | 24 GB | 24 GB | **GPU-S** | 图像 |
| **Stable Diffusion 3.5 Large** 🔒 受限 | stabilityai/stable-diffusion-3.5-large | 16 GB | 18 GB | **GPU-S** | 图像 |
| **Stable Diffusion 3.5 Medium** 🔒 受限 | stabilityai/stable-diffusion-3.5-medium | 5 GB | 10 GB | **GPU-S** | 图像 |
| **HiDream-I1 Full** | HiDream-ai/HiDream-I1-Full | 34 GB | 40 GB | **GPU-S** | 图像 |
| **Wan 2.2 T2V A14B** | Wan-AI/Wan2.2-T2V-A14B | 28 GB | 40 GB | **GPU-S** | 视频 |
| **Wan 2.1 T2V 1.3B (low VRAM)** | Wan-AI/Wan2.1-T2V-1.3B | 3 GB | 8 GB | **GPU-S** | 视频 |
| **HunyuanVideo 1.5 (8.3B)** | tencent/HunyuanVideo-1.5 | 17 GB | 24 GB | **GPU-S** | 视频 |
| **LTX-Video 0.9.8 13B** | Lightricks/LTX-Video | 26 GB | 24 GB | **GPU-S** | 视频 |
| **CogVideoX-5B** | zai-org/CogVideoX-5b | 10 GB | 16 GB | **GPU-S** | 视频 |
| **Whisper Large v3 Turbo** | openai/whisper-large-v3-turbo | 2 GB | 4 GB | **GPU-S** | 音频 |
| **Whisper Large v3** | openai/whisper-large-v3 | 3 GB | 6 GB | **GPU-S** | 音频 |
| **Kokoro 82M (TTS)** | hexgrad/Kokoro-82M | 1 GB | 2 GB | **GPU-S** | 音频 |
| **Sesame CSM-1B (conversational TTS)** | sesame/csm-1b | 2 GB | 6 GB | **GPU-S** | 音频 |
| **Stable Audio Open 1.0** 🔒 受限 | stabilityai/stable-audio-open-1.0 | 3 GB | 8 GB | **GPU-S** | 音频 |



大小为 FP16 权重。RTX 4090（24 GB VRAM）运行 70B 模型时，AWQ 量化版本将并行自动下载。

横向对比


## ServPrivate vs Vast.ai · RunPod · Paperspace · Lambda Labs · TensorDock



纯加密货币结账、原生 Monero、仅 Token 注册、预装 AI 技术栈、预下载 HuggingFace 模型、加密 HF Token、自动 Let's Encrypt 端点、无限带宽及冰岛 100% 可再生能源——查看"ServPrivate"那行，自行判断。



| 功能 | ServPrivate | Vast.ai | RunPod | Paperspace | Lambda | TensorDock |
| --- | --- | --- | --- | --- | --- | --- |
| **纯加密货币结账** | ✅ 20 coins | ⚠️ BTC | ⚠️ Gateway | ❌ | ❌ | ⚠️ BTC/ETH/USDT |
| **原生 Monero (XMR)** | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| **无 KYC，无需邮箱注册** | ✅ Token-only | ⚠️ Email + ID for trust | ⚠️ Email + payment | ❌ Full KYC | ❌ Enterprise KYC | ⚠️ Email + light KYC |
| **预装 AI 技术栈** | ✅ 17 templates | ⚠️ Docker BYO | ✅ 100+ | ⚠️ Notebooks only | ⚠️ Lambda Stack only | ⚠️ Docker BYO |
| **下单时预下载模型** | ✅ 27 models | ❌ | ❌ | ❌ | ❌ | ❌ |
| **下单时提交 HuggingFace Token** | ✅ Encrypted, used once | ❌ | ❌ | ❌ | ❌ | ❌ |
| **下单时提交 SSH 密钥** | ✅ | ✅ | ✅ | ⚠️ | ✅ | ⚠️ |
| **自动关机计时器** | ✅ 6h-7d | ✅ | ⚠️ Spot only | ❌ | ❌ | ❌ |
| **公共 HTTPS 端点（Let's Encrypt）** | ✅ Auto | ⚠️ Manual | ✅ Pods | ✅ | ❌ | ⚠️ Manual |
| **无限带宽** | ✅ | ⚠️ Per host | ⚠️ Capped | ⚠️ Capped | ⚠️ Capped | ⚠️ Per host |
| **可再生能源数据中心** | ✅ Iceland 100% geo+hydro | ❌ Variable | ⚠️ US grid | ⚠️ US grid | ⚠️ US grid | ⚠️ Variable |
| **离岸司法管辖** | ✅ IS / NL / RO / MD | ❌ Distributed P2P | ❌ US-centric | ❌ US | ❌ US-only | ⚠️ Multi-region |
| **沙盒演练模式** | ✅ ?dry_run=1 | ⚠️ Trial credit | ⚠️ Limited | ⚠️ Free GPU tier | ❌ | ❌ |
| **AI 代理 / MCP 优先** | ✅ MCP + REST + x402 | ⚠️ REST | ⚠️ REST | ⚠️ REST | ⚠️ REST | ⚠️ REST |
| **入门款 RTX 4090 / 月** | **$122.00** | ~$216 spot | ~$396 on-demand | n/a | n/a | ~$252 spot |



比较数据来源于竞争对手 2026-05 公开定价页面及注册流程。ServPrivate 入门款 RTX 4090 = 摩尔多瓦 $122.00/月；竞争对手"现货"价格为同等硬件的平均费率。

常见问题

## GPU AI 托管常见问题





### 01
GPU 是完整硬件直通，还是共享 / vGPU 切片？



完整硬件直通。您独占整块物理 NVIDIA 显卡，直接访问 VRAM — 不是 vGPU 切片，不是时分复用的 MIG 分区。虚拟机内的 nvidia-smi 显示与裸金属宿主机相同的数据。完整驱动访问，完整 CUDA，完整 PyTorch / TensorFlow 栈 — 无 SR-IOV 保留。





### 02
预装了哪些 CUDA / 驱动版本？



默认镜像：Ubuntu 22.04 + CUDA 12.4 + cuDNN 9 + NVIDIA 驱动 550。其他即用镜像：Ubuntu 24.04 + CUDA 12.6、Ubuntu 22 + PyTorch 2.5、Ubuntu 22 + ComfyUI + Flux、Ubuntu 22 + Ollama + Open WebUI。如需自行安装，也提供原版 Ubuntu / Debian / AlmaLinux / Rocky。您可以随时以完全 root 权限切换驱动版本。





### 03
我可以在这些 GPU 上运行自己 AI 初创公司的生产推理吗？



可以。我们许多 GPU 客户在 vLLM / TGI / FastAPI 之上运行公共推理 API。GPU 服务器提供完全 root、可预测的月度账单（无按 token 计费意外）及固定的司法管辖区 IP。所有 GPU 方案均提供无限带宽，您可以提供高流量公共端点，无需监控流量计或支付超额费用。





### 04
为何 Russia 被排除在 GPU 地区之外？



NVIDIA H100、A100 及高端 RTX 显卡（4090 及以上）受美国商务部出口管制（15 CFR Part 744）及欧盟两用品法规约束，禁止运往俄罗斯数据中心。为遵守适用于我们供应链的管制规定，我们不在 Russia 部署这些产品。如果您需要在 Russia 部署离岸 Linux VPS 或独立服务器，这些产品线不受影响。





### 05
为何 Iceland 被定位为高端 GPU 地区？



Iceland 数据中心 100% 使用可再生地热与水力发电，寒冷的环境温度在持续满载时显著降低了每台 700W H100 机器的冷却开销。最终提供市场上碳排放最低的离岸 GPU 算力。溢价涵盖了 Iceland 较高的数据中心成本与更清洁的能源来源 — 对于 ESG 意识 AI 团队，这是唯一可信的离岸选择。





### 06
我可以使用多块 GPU 进行分布式训练（DDP / FSDP）吗？



可以 — GPU-XL 层级配备 2× H100 SXM5，通过 NVLink 互联于同一机箱内，非常适合在同一台机器上运行 FSDP / DeepSpeed Zero-3 / DDP。对于多节点训练，您可以在同一数据中心租用多台 GPU-XL 服务器，并通过 10 Gbps 上行链路互联。我们目前不提供 8× H100 集群节点 — 如您的训练规模需要更大容量，请联系我们。






## 部署您的离岸 GPU 服务器



选择司法管辖区，选择 NVIDIA GPU，以 20 种加密货币之一付款。60 秒内获得实时 JupyterLab。无 KYC，无邮箱，无手机 — 仅需一个令牌。

[查看 GPU 方案](#plans)


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}
```

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}
```

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}
```

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            "position": 15,
            "url": "https://servprivate.com/order?type=gpu&plan=NL-L&location=netherlands",
            "name": "NL-L — 荷兰"
        },
        {
            "@type": "ListItem",
            "position": 16,
            "url": "https://servprivate.com/order?type=gpu&plan=NL-XL&location=netherlands",
            "name": "NL-XL — 荷兰"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "FAQPage",
    "mainEntity": [
        {
            "@type": "Question",
            "name": "GPU 是完整硬件直通，还是共享 / vGPU 切片？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "完整硬件直通。您独占整块物理 NVIDIA 显卡，直接访问 VRAM — 不是 vGPU 切片，不是时分复用的 MIG 分区。虚拟机内的 nvidia-smi 显示与裸金属宿主机相同的数据。完整驱动访问，完整 CUDA，完整 PyTorch / TensorFlow 栈 — 无 SR-IOV 保留。"
            }
        },
        {
            "@type": "Question",
            "name": "预装了哪些 CUDA / 驱动版本？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "默认镜像：Ubuntu 22.04 + CUDA 12.4 + cuDNN 9 + NVIDIA 驱动 550。其他即用镜像：Ubuntu 24.04 + CUDA 12.6、Ubuntu 22 + PyTorch 2.5、Ubuntu 22 + ComfyUI + Flux、Ubuntu 22 + Ollama + Open WebUI。如需自行安装，也提供原版 Ubuntu / Debian / AlmaLinux / Rocky。您可以随时以完全 root 权限切换驱动版本。"
            }
        },
        {
            "@type": "Question",
            "name": "我可以在这些 GPU 上运行自己 AI 初创公司的生产推理吗？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "可以。我们许多 GPU 客户在 vLLM / TGI / FastAPI 之上运行公共推理 API。GPU 服务器提供完全 root、可预测的月度账单（无按 token 计费意外）及固定的司法管辖区 IP。所有 GPU 方案均提供无限带宽，您可以提供高流量公共端点，无需监控流量计或支付超额费用。"
            }
        },
        {
            "@type": "Question",
            "name": "为何 Russia 被排除在 GPU 地区之外？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "NVIDIA H100、A100 及高端 RTX 显卡（4090 及以上）受美国商务部出口管制（15 CFR Part 744）及欧盟两用品法规约束，禁止运往俄罗斯数据中心。为遵守适用于我们供应链的管制规定，我们不在 Russia 部署这些产品。如果您需要在 Russia 部署离岸 Linux VPS 或独立服务器，这些产品线不受影响。"
            }
        },
        {
            "@type": "Question",
            "name": "为何 Iceland 被定位为高端 GPU 地区？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "Iceland 数据中心 100% 使用可再生地热与水力发电，寒冷的环境温度在持续满载时显著降低了每台 700W H100 机器的冷却开销。最终提供市场上碳排放最低的离岸 GPU 算力。溢价涵盖了 Iceland 较高的数据中心成本与更清洁的能源来源 — 对于 ESG 意识 AI 团队，这是唯一可信的离岸选择。"
            }
        },
        {
            "@type": "Question",
            "name": "我可以使用多块 GPU 进行分布式训练（DDP / FSDP）吗？",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "可以 — GPU-XL 层级配备 2× H100 SXM5，通过 NVLink 互联于同一机箱内，非常适合在同一台机器上运行 FSDP / DeepSpeed Zero-3 / DDP。对于多节点训练，您可以在同一数据中心租用多台 GPU-XL 服务器，并通过 10 Gbps 上行链路互联。我们目前不提供 8× H100 集群节点 — 如您的训练规模需要更大容量，请联系我们。"
            }
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "BreadcrumbList",
    "itemListElement": [
        {
            "@type": "ListItem",
            "position": 1,
            "name": "首页",
            "item": "https://servprivate.com/"
        },
        {
            "@type": "ListItem",
            "position": 2,
            "name": "GPU AI 托管",
            "item": "https://servprivate.com/gpu"
        }
    ]
}
```

```json
{
    "@context": "https://schema.org",
    "@type": "WebAPI",
    "name": "ServPrivate Agent API",
    "description": "Public REST API + MCP server. Agents can purchase a GPU server in 2 calls. No KYC, crypto-only.",
    "documentation": "https://servprivate.com/agents",
    "termsOfService": "https://servprivate.com/tos",
    "provider": {
        "@id": "https://servprivate.com/#organization"
    },
    "potentialAction": {
        "@type": "BuyAction",
        "target": {
            "@type": "EntryPoint",
            "urlTemplate": "https://servprivate.com/api/v1/orders",
            "httpMethod": "POST",
            "contentType": "application/json"
        },
        "object": {
            "@id": "https://servprivate.com/gpu#product"
        }
    }
}
```