# GPUX.AI 根据 OpenAITools.app 于 2026-11-11 核对的流量数据，GPUX.AI（gpux.ai）是一个收录在 AI API 下的 AI 平台，月访问量为 68，月度环比流量变化为 -649（-90.5%）。其主要地理市场为印度尼西亚（100% 流量份额），采用定价请咨询定价模式。按月流量计算的主要竞争替代方案包括 BytePlus（303.61万次访问/月），Together AI（164.59万次访问/月），DeepInfra（45.78万次访问/月）。 GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models. ## 关键遥测与规格 | 指标 | 数值 | | :--- | :--- | | 工具名称 | GPUX.AI | | 标识 | gpux-ai | | Status | active | | Origin | independent | | Maintenance | active | | 官方域名 | gpux.ai | | 官网地址 | https://gpux.ai | | 分类 | AI API, AI Models, AI Developer Tools, AI Image Generator, AI 语音转文字, Large Language Models (LLMs) | | 定价模式 | 定价请咨询 | | 月访问量 | 68 | | 月度环比流量变化 | -649 | | 月度环比增长率 | -90.5% | | 主要市场 | 印度尼西亚 | | 市场份额 | 100% | | 直接访问量 | 27 | | 自然搜索访问 | 0 | | 社交访问 | 0 | | 推荐访问 | 6 | | 邮件访问 | 1 | | 评价得分 | 3.5 | | 收藏数 | 0 | | 支持平台 | 网站 | | 计费平台 | | | 属性 | 功能: 网站; 定价: 定价请咨询 | | 标签 | GPU, Docker, 推理, 无服务器, AI, 机器学习, StableDiffusion, 模型部署 | ## 概览 GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models. ## 定价与套餐 Contact for pricing. GPUX.AI does not publish public plan tiers or per-GPU rates on its site; pricing is arranged through a sales conversation, with a 'Talk to a Founder' booking link as the entry point. ## 关键功能与能力 - **Dockerized app deployment:** Package AI applications as Docker images and run them on GPU infrastructure with claimed cold starts around one second, so you do not manage servers yourself. - **Serverless inference over HTTP:** Invoke models over HTTP — the site advertises a single curl call for Stable Diffusion XL — and pay for what you use rather than idle GPU time. - **Monetize private models:** Host a private model and sell inference requests to other organizations, turning your model into a product. - **GPU routing and cold starts:** Route inference across GPUs with an emphasis on cold-start performance and efficient scheduling for bursty workloads. - **Prebuilt model examples:** Reference deployments for Stable Diffusion, SDXL, ESRGAN and Whisper show how image generation and speech-to-text workloads are wired up. ## 主要用例 - **Serverless image generation (ML engineer):** Run diffusion and upscaling models on demand instead of provisioning and maintaining dedicated GPU servers, paying only for requests served. - **Host and monetize a private model (AI startup founder):** Containerize a model, expose it over HTTP and sell inference requests to other organizations without building billing and routing infrastructure. - **Deploy custom AI containers (Backend developer):** Use Docker to deploy custom pipelines that a fixed-model API cannot support, keeping your existing container tooling. - **Batch transcription workloads (Media or audio team):** Run Whisper-family speech-to-text through an HTTP endpoint as part of a transcription or media-processing workflow. - **Earn on idle GPU hardware (Compute contributor):** Contribute spare Windows or Linux GPU capacity via the open-source edge agent on GitHub. ## 优势 - Docker-based deployment lets you run arbitrary AI applications, not just a fixed model catalog. - Cold-start performance is a stated core focus, which matters for bursty serverless inference. - Inference is callable over simple HTTP, illustrated by a one-line curl example. - Private models can be monetized by selling requests to other organizations. - Open-source edge agent on GitHub extends the platform's model to spare machines. ## 局限 - Marketing content has not been refreshed recently, so it is hard to tell how actively the platform is maintained. - The hosted dashboard and inference endpoint were not reachable during this audit, which is a real risk for a service you would build on. - Documentation is light compared with larger serverless GPU providers. - 'Contact for pricing' means you cannot self-serve a cost estimate before talking to sales. - Docker-based deployment has a learning curve if you are used to notebook-style workflows. ## 常见问题 ### What is GPUX.AI? GPUX.AI is a serverless GPU platform. You deploy Dockerized applications, run inference workloads such as Stable Diffusion and Whisper, and can sell requests on your own private models to other organizations. It advertises cold starts from around one second. ### How much does GPUX.AI cost? GPUX.AI does not publish public plan pricing; engagement is by contact and a 'Talk to a Founder' booking link. Because it targets GPU workloads sold on usage and private model hosting, cost depends on what you deploy. ### What kind of AI workloads does it run? It is built around Docker, which means you can package arbitrary AI applications rather than only calling a fixed set of hosted models. The site highlights Stable Diffusion XL, ESRGAN and Whisper as examples, including a one-line curl call for SDXL. ### Can I sell access to my own model? Yes. A documented use case is selling requests on your private model to other organizations, so you can monetize a model you host rather than only consuming compute. ### Is the platform actively available? The homepage was live during this audit but the hosted app and inference endpoint subdomains were not reachable at the same time, and the site's own news stops in 2023. Confirm current service availability with the team before committing production workloads. ### GPUX.AI 的月流量和增长趋势如何？ GPUX.AI 目前每月获得 68 访问量，月度环比流量变化为 -649（增长率 -90.5%）。其主要来源市场是印度尼西亚（100% 份额），包括每月 27 次直接访问和每月 0 次自然搜索访问。 ### GPUX.AI 免费吗？它的定价模式是什么？ GPUX.AI 采用定价请咨询定价模式。Contact for pricing. GPUX.AI does not publish public plan tiers or per-GPU rates on its site; pricing is arranged through a sales conversation, with a 'Talk to a Founder' booking link as the entry point. 支持的计费和结账平台包括：未列出。 ### 2026 年 GPUX.AI 的最佳替代方案有哪些？ 基于 OpenAITools.app 的分类流量和功能契合度，GPUX.AI 的前五个替代方案是：1. BytePlus（303.61万次访问/月）; 2. Together AI（164.59万次访问/月）; 3. DeepInfra（45.78万次访问/月）; 4. fal.ai（309.37万次访问/月）; 5. Runware（40.29万次访问/月）。 ### GPUX.AI 支持哪些平台和核心 AI 能力？ GPUX.AI 被归类在 AI API, AI Models, AI Developer Tools, AI Image Generator 下，支持以下平台：网站，其核心能力标签包括：GPU, Docker, 推理, 无服务器, AI, 机器学习。 ## 替代工具 | 工具名称 | 月访问量 | 定价模式 | 对比 | | :--- | :--- | :--- | :--- | | [BytePlus](https://openaitools.app/zh/tool/byteplus) | 3,036,127 | 免费增值，付费 | [对比](https://openaitools.app/zh/compare/byteplus-vs-gpux-ai) | | [Together AI](https://openaitools.app/zh/tool/together-ai) | 1,645,930 | 免费增值，付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-together-ai) | | [DeepInfra](https://openaitools.app/zh/tool/deep-infra) | 457,810 | 付费 | [对比](https://openaitools.app/zh/compare/deep-infra-vs-gpux-ai) | | [fal.ai](https://openaitools.app/zh/tool/fal-ai) | 3,093,684 | Paid, pay-as-you-go usage-based pricing | [对比](https://openaitools.app/zh/compare/fal-ai-vs-gpux-ai) | | [Runware](https://openaitools.app/zh/tool/runware) | 402,862 | 付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-runware) | | [Novita AI](https://openaitools.app/zh/tool/novita-ai) | 271,371 | 付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-novita-ai) | | [Replicate AI](https://openaitools.app/zh/tool/replicate-ai) | 904,038 | 付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-replicate-ai) | | [OpenAI 平台](https://openaitools.app/zh/tool/openai) | 234,678,639 | 付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-openai) | | [Chutes](https://openaitools.app/zh/tool/chutes) | 250,187 | 付费 | [对比](https://openaitools.app/zh/compare/chutes-vs-gpux-ai) | | [Synexa AI](https://openaitools.app/zh/tool/synexa-ai) | 7,179 | 付费 | [对比](https://openaitools.app/zh/compare/gpux-ai-vs-synexa-ai) | | [Google AI Studio](https://openaitools.app/zh/tool/google-ai-studio) | 112,620,020 | 免费增值 | [对比](https://openaitools.app/zh/compare/google-ai-studio-vs-gpux-ai) | | [Fireworks](https://openaitools.app/zh/tool/fireworks-ai) | 659,687 | 定价请咨询 | [对比](https://openaitools.app/zh/compare/fireworks-ai-vs-gpux-ai) | ## 社区 GPUX.AI 社区：交流在 GPU 上运行 AI 推理与 Docker 化应用、通过 HTTP 端点部署模型，以及在 Windows 10 或 Linux 上共享 GPU 算力的经验。 [GPUX.AI](https://discord.com/invite/jjBSjSF) --- 来源：https://openaitools.app/zh/tool/gpux-ai