# GPUX.AI

2026-11-11에 검증된 OpenAITools.app 텔레메트리에 따르면, GPUX.AI(gpux.ai)은(는) AI API에 색인된 AI 플랫폼으로 월 68회 방문을 기록 중이며, 전월 대비 트래픽 변화량은 -649(-90.5%)입니다. 주요 지리적 시장은 인도네시아(트래픽 점유율 100%)이며, 가격 문의 가격 모델로 운영됩니다. 월간 트래픽 기준 주요 경쟁 대안으로는 BytePlus (월 303.61만회 방문), Together AI (월 164.59만회 방문), DeepInfra (월 45.78만회 방문) 등이 있습니다.

GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models.

## 주요 텔레메트리 및 사양

| 지표 | 값 |
| :--- | :--- |
| 도구 이름 | GPUX.AI |
| 핸들 | gpux-ai |
| Status | active |
| Origin | independent |
| Maintenance | active |
| 공식 도메인 | gpux.ai |
| 웹사이트 URL | https://gpux.ai |
| 카테고리 | AI API, AI 모델, AI 개발자 도구, AI 이미지 생성기, AI 음성-텍스트 변환, Large Language Models (LLMs) |
| 가격 모델 | 가격 문의 |
| 월간 방문 수 | 68 |
| 전월 대비 트래픽 변화 | -649 |
| 전월 대비 성장률 | -90.5% |
| 주요 시장 | 인도네시아 |
| 시장 점유율 | 100% |
| 직접 방문 | 27 |
| 자연 검색 방문 | 0 |
| 소셜 방문 | 0 |
| 추천 방문 | 6 |
| 이메일 방문 | 1 |
| 리뷰 점수 | 3.5 |
| 저장 수 | 0 |
| 지원 플랫폼 | 웹사이트 |
| 결제 플랫폼 |  |
| 속성 | 기능: 웹사이트; 가격: 가격 문의 |
| 태그 | GPU, Docker, 추론, 서버리스, AI, 머신러닝, StableDiffusion, 모델 배포 |

## 개요

GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models.

## 가격 및 요금제

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.

## 주요 기능 및 역량

- **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.

## 주요 활용 사례

- **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.

## 강점

- 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.

## 한계

- 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.

## 자주 묻는 질문

### 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.AI의 월간 트래픽과 성장 추세는 어떠한가요?
GPUX.AI은(는) 현재 월 68회 방문을 기록 중이며, 전월 대비 트래픽 변화량은 -649(성장률 -90.5%)입니다. 주요 유입 시장은 인도네시아(점유율 100%)이며, 여기에는 월 직접 방문 27회와 월 자연 검색 방문 0회가 포함됩니다.

### GPUX.AI은(는) 무료인가요? 가격 모델은 무엇인가요?
GPUX.AI은(는) 가격 문의 가격 모델로 운영됩니다. 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. 지원되는 결제 및 체크아웃 플랫폼에는 등록되지 않음 등이 있습니다.

### 2026년 최고의 GPUX.AI 대안은 무엇인가요?
OpenAITools.app의 카테고리 트래픽과 기능 적합도를 기준으로 할 때 GPUX.AI의 상위 5개 대안은 다음과 같습니다: 1. BytePlus (월 303.61만회 방문); 2. Together AI (월 164.59만회 방문); 3. DeepInfra (월 45.78만회 방문); 4. fal.ai (월 309.37만회 방문); 5. Runware (월 40.29만회 방문).

### GPUX.AI은(는) 어떤 플랫폼과 핵심 AI 역량을 지원하나요?
GPUX.AI은(는) AI API, AI 모델, AI 개발자 도구, AI 이미지 생성기으로 분류되며 다음 플랫폼을 지원합니다: 웹사이트. 핵심 역량 태그에는 GPU, Docker, 추론, 서버리스, AI, 머신러닝 등이 있습니다.

## 대안

| 도구 이름 | 월간 방문 수 | 가격 모델 | 비교 |
| :--- | :--- | :--- | :--- |
| [BytePlus](https://openaitools.app/ko/tool/byteplus) | 3,036,127 | 무료+유료, 유료 | [비교](https://openaitools.app/ko/compare/byteplus-vs-gpux-ai) |
| [Together AI](https://openaitools.app/ko/tool/together-ai) | 1,645,930 | 무료+유료, 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-together-ai) |
| [DeepInfra](https://openaitools.app/ko/tool/deep-infra) | 457,810 | 유료 | [비교](https://openaitools.app/ko/compare/deep-infra-vs-gpux-ai) |
| [fal.ai](https://openaitools.app/ko/tool/fal-ai) | 3,093,684 | Paid, pay-as-you-go usage-based pricing | [비교](https://openaitools.app/ko/compare/fal-ai-vs-gpux-ai) |
| [Runware](https://openaitools.app/ko/tool/runware) | 402,862 | 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-runware) |
| [Novita AI](https://openaitools.app/ko/tool/novita-ai) | 271,371 | 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-novita-ai) |
| [Replicate AI](https://openaitools.app/ko/tool/replicate-ai) | 904,038 | 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-replicate-ai) |
| [OpenAI 플랫폼](https://openaitools.app/ko/tool/openai) | 234,678,639 | 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-openai) |
| [Chutes](https://openaitools.app/ko/tool/chutes) | 250,187 | 유료 | [비교](https://openaitools.app/ko/compare/chutes-vs-gpux-ai) |
| [Synexa AI](https://openaitools.app/ko/tool/synexa-ai) | 7,179 | 유료 | [비교](https://openaitools.app/ko/compare/gpux-ai-vs-synexa-ai) |
| [Google AI Studio](https://openaitools.app/ko/tool/google-ai-studio) | 112,620,020 | 무료+유료 | [비교](https://openaitools.app/ko/compare/google-ai-studio-vs-gpux-ai) |
| [Fireworks](https://openaitools.app/ko/tool/fireworks-ai) | 659,687 | 가격 문의 | [비교](https://openaitools.app/ko/compare/fireworks-ai-vs-gpux-ai) |

## 커뮤니티

GPUX.AI 커뮤니티: GPU에서 AI 추론과 도커화된 앱을 실행하고, HTTP 엔드포인트로 모델을 배포하며, Windows 10 또는 Linux에서 GPU를 공유하는 방법을 논의합니다.

[GPUX.AI](https://discord.com/invite/jjBSjSF)

---
출처: https://openaitools.app/ko/tool/gpux-ai