# GPUX.AI OpenAITools.app のテレメトリ（2026-11-11 検証）によると、GPUX.AI（gpux.ai）は AI API に分類される AI プラットフォームで、月間 68 の訪問を生み出し、前月比のトラフィック増減は -649（-90.5%）です。主要な地域市場はインドネシア（トラフィックシェア 100%）で、料金は要問い合わせの料金モデルで運営されています。月間ボリューム別の主な競合代替ツールには BytePlus（月間 303.61万訪問）、Together AI（月間 164.59万訪問）、DeepInfra（月間 45.78万訪問）が含まれます。 GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models. ## 主なテレメトリと仕様 | 指標 | 値 | | :--- | :--- | | ツール名 | GPUX.AI | | ハンドル | gpux-ai | | Status | active | | Origin | independent | | Maintenance | active | | 公式ドメイン | gpux.ai | | ウェブサイト URL | https://gpux.ai | | カテゴリ | AI API, AIモデル, AI開発者ツール, AI画像生成, AI 音声テキスト化, Large Language Models (LLMs) | | 料金モデル | 料金は要問い合わせ | | 月間訪問数 | 68 | | 前月比トラフィック変動 | -649 | | 前月比成長率 | -90.5% | | 主要市場 | インドネシア | | 市場シェア | 100% | | ダイレクト訪問 | 27 | | オーガニック検索訪問 | 0 | | ソーシャル訪問 | 0 | | リファラル訪問 | 6 | | メール訪問 | 1 | | レビュースコア | 3.5 | | 保存数 | 0 | | 対応プラットフォーム | ウェブサイト | | 請求プラットフォーム | | | 属性 | 機能: ウェブサイト; 料金: 料金は要問い合わせ | | タグ | GPU, Docker, 推論, サーバーレス, AI, 機械学習, StableDiffusion, モデル展開 | ## 概要 GPUX.AI is a serverless GPU platform for deploying Dockerized AI applications, running inference on demand and selling access to your own private models. ## 料金とプラン 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. ## 主な機能と特長 - **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. ## 主なユースケース - **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. ## 強み - 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. ## 制約・デメリット - 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. ## よくある質問 ### 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 の月間トラフィックと成長トレンドはどうですか？ GPUX.AI は現在、月間 68 の訪問があり、前月比のトラフィック変動は -649（成長率 -90.5%）です。主要な流入市場はインドネシア（シェア 100%）で、月間 27 のダイレクト訪問と月間 0 のオーガニック検索訪問を含みます。 ### GPUX.AI は無料ですか？料金モデルは何ですか？ GPUX.AI は料金は要問い合わせの料金モデルで運営されています。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. 対応する請求・チェックアウトプラットフォームには未掲載が含まれます。 ### 2026年における GPUX.AI の最適な代替ツールはどれですか？ OpenAITools.app のカテゴリ別トラフィックと機能の適合性に基づくと、GPUX.AI の代替ツールトップ5は次のとおりです: 1. BytePlus（月間 303.61万訪問）; 2. Together AI（月間 164.59万訪問）; 3. DeepInfra（月間 45.78万訪問）; 4. fal.ai（月間 309.37万訪問）; 5. Runware（月間 40.29万訪問）。 ### GPUX.AI はどのプラットフォームと主要な AI 機能に対応していますか？ GPUX.AI は AI API, AIモデル, AI開発者ツール, AI画像生成に分類され、以下のプラットフォームに対応しています: ウェブサイト。中核機能のタグには GPU, Docker, 推論, サーバーレス, AI, 機械学習が含まれます。 ## 代替ツール | ツール名 | 月間訪問数 | 料金モデル | 比較 | | :--- | :--- | :--- | :--- | | [BytePlus](https://openaitools.app/ja/tool/byteplus) | 3,036,127 | フリーミアム、有料 | [比較](https://openaitools.app/ja/compare/byteplus-vs-gpux-ai) | | [Together AI](https://openaitools.app/ja/tool/together-ai) | 1,645,930 | フリーミアム、有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-together-ai) | | [DeepInfra](https://openaitools.app/ja/tool/deep-infra) | 457,810 | 有料 | [比較](https://openaitools.app/ja/compare/deep-infra-vs-gpux-ai) | | [fal.ai](https://openaitools.app/ja/tool/fal-ai) | 3,093,684 | Paid, pay-as-you-go usage-based pricing | [比較](https://openaitools.app/ja/compare/fal-ai-vs-gpux-ai) | | [Runware](https://openaitools.app/ja/tool/runware) | 402,862 | 有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-runware) | | [Novita AI](https://openaitools.app/ja/tool/novita-ai) | 271,371 | 有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-novita-ai) | | [Replicate AI](https://openaitools.app/ja/tool/replicate-ai) | 904,038 | 有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-replicate-ai) | | [OpenAI プラットフォーム](https://openaitools.app/ja/tool/openai) | 234,678,639 | 有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-openai) | | [Chutes](https://openaitools.app/ja/tool/chutes) | 250,187 | 有料 | [比較](https://openaitools.app/ja/compare/chutes-vs-gpux-ai) | | [Synexa AI](https://openaitools.app/ja/tool/synexa-ai) | 7,179 | 有料 | [比較](https://openaitools.app/ja/compare/gpux-ai-vs-synexa-ai) | | [Google AI Studio](https://openaitools.app/ja/tool/google-ai-studio) | 112,620,020 | フリーミアム | [比較](https://openaitools.app/ja/compare/google-ai-studio-vs-gpux-ai) | | [Fireworks](https://openaitools.app/ja/tool/fireworks-ai) | 659,687 | 料金は要問い合わせ | [比較](https://openaitools.app/ja/compare/fireworks-ai-vs-gpux-ai) | ## コミュニティ GPUX.AI コミュニティ：GPU 上での AI 推論と Docker 化アプリの実行、HTTP エンドポイント経由のモデルデプロイ、Windows 10 や Linux での GPU 共有に関する情報交換の場です。 [GPUX.AI](https://discord.com/invite/jjBSjSF) --- 出典: https://openaitools.app/ja/tool/gpux-ai