# Runware

OpenAITools.app のテレメトリ（2026-11-11 検証）によると、Runware（runware.ai）は AI API に分類される AI プラットフォームで、月間 40.29万の訪問を生み出し、前月比のトラフィック増減は +8.58万（+27.1%）です。主要な地域市場はアメリカ合衆国（トラフィックシェア 27.3%）で、有料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 fal.ai（月間 309.37万訪問）、Replicate AI（月間 90.4万訪問）、Novita AI（月間 27.14万訪問）が含まれます。

Runware is an AI inference platform that exposes an enormous model catalog — images, video, audio, LLMs and 3D — through a single API endpoint, alongside serverless GPU compute and reserved capacity running on modular data centers the company designs and operates itself. It is aimed at developers and product teams who want to ship generative features without managing infrastructure.

## 主なテレメトリと仕様

| 指標 | 値 |
| :--- | :--- |
| ツール名 | Runware |
| ハンドル | runware |
| Status | active |
| Origin | independent |
| Maintenance | active |
| 公式ドメイン | runware.ai |
| ウェブサイト URL | https://runware.ai |
| カテゴリ | AI API, AI画像生成, Text to Image, AIモデル, AI開発者ツール, AI 背景除去ツール, AI インペインティング, AI アウトペインティング, AI画像アップスケーラー |
| 料金モデル | 有料 |
| 月間訪問数 | 402,862 |
| 前月比トラフィック変動 | 85,780 |
| 前月比成長率 | +27.1% |
| 主要市場 | アメリカ合衆国 |
| 市場シェア | 27.3% |
| ダイレクト訪問 | 189,796 |
| オーガニック検索訪問 | — |
| ソーシャル訪問 | — |
| リファラル訪問 | 12,281 |
| メール訪問 | 6,048 |
| レビュースコア | 4.5 |
| 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: 有料 |
| タグ | Stable Diffusion API, 画像生成, 生成AI, AIプラットフォーム, 画像編集, 機械学習, 深層学習, API, モデル, 推論, 低コスト, 高速推論, 再生可能エネルギー, カスタムハードウェア |

## 概要

Runware is an AI inference platform that exposes an enormous model catalog — images, video, audio, LLMs and 3D — through a single API endpoint, alongside serverless GPU compute and reserved capacity running on modular data centers the company designs and operates itself. It is aimed at developers and product teams who want to ship generative features without managing infrastructure.

## 料金とプラン

Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales.

## 主な機能と特長

- **One API for every modality:** Image, video, audio, LLM and 3D tasks all POST to a single endpoint as an array, so mixed-modality batches can travel in one request with shared auth and billing.
- **400K+ model catalog:** Browse hosted, partner and community models through one addressing scheme, control parameters such as stacked LoRAs and swapped VAEs on open models, and add your own uploads.
- **Serverless and reserved GPU compute:** Bring your own container and weights to serverless GPUs billed by the second that scale to zero when idle, or commit to reserved capacity and bare-metal clusters for a lower per-hour rate.
- **Sonic Pods and the Sonic Inference Engine:** Purpose-built modular data centers plus an orchestration layer that keeps weights preloaded across regions and routes requests to pods that already hold the model in memory.
- **Developer tooling and agent integrations:** A hosted MCP server, CLI, skill files, playground, model schemas and llms.txt let you wire Runware into Claude Code, Cursor, Codex or any MCP-capable client with minimal setup.
- **Enterprise-grade trust and compliance:** SOC 2, ISO 27001 and GDPR compliance, EU and US data residency, SSO/SAML, configurable MFA, a strict no-training-on-customer-data policy and optional Zero Data Retention.

## 主なユースケース

- **Ship generative features without infrastructure (Product engineer):** Call one consistent API for image, video, audio and language tasks so your team avoids maintaining separate vendor integrations and multiple billing relationships.
- **Control inference cost at scale (AI startup founder):** Use pay-per-use model APIs for experimentation, then move predictable workloads to reserved GPU capacity to cut per-hour compute costs as traffic grows.
- **Deploy your own weights (Fine-tuning and custom model owner):** Upload private model weights or bring a container and run them on serverless GPUs, keeping the artifacts private and billed only for the seconds used.
- **Consolidate vendor sprawl (Platform or MLOps lead):** Standardize on one endpoint, one key and one invoice across modalities, while gaining SOC 2, ISO 27001 and data-residency controls for compliance review.
- **Give agents image and media tooling (Agent developer):** Connect the hosted MCP server so coding agents and assistants can generate and edit images, video and audio directly through tool calls.

## 強み

- Unusually broad catalog — hundreds of thousands of models behind one consistent endpoint and API key
- Aggressive published pricing, with claims of up to 10x lower cost per generation than market rates
- Both managed inference and raw compute in one platform, so you can migrate from API calls to your own containers without changing vendors
- Real infrastructure differentiation through self-designed modular data centers rather than reselling someone else's capacity
- Strong compliance posture for an AI API vendor: SOC 2, ISO 27001, GDPR, EU/US residency, SSO/SAML and Zero Data Retention
- Billing only for successful requests, plus $2 in free credits for business-email signups

## 制約・デメリット

- The breadth of the catalog and the mix of hosted, partner and community models can be overwhelming when choosing a model
- Only a subset of models (currently around 300+) has published pricing on the rate sheet, so some community models require checking the playground for cost
- LLM billing splits input, output and cache-read token dimensions, adding complexity to cost forecasting
- Bare-metal and high-volume reserved capacity are sales-gated rather than self-serve
- Published savings figures are Runware's own comparisons and should be validated against your particular workload

## よくある質問

### What is Runware, in one sentence?
Runware is an AI inference platform offering a single API across hundreds of thousands of image, video, audio, LLM and 3D models, together with serverless GPU compute and reserved capacity on its own modular data centers.

### How does billing work?
It is pay-as-you-go with no subscription. You are billed per generation, per second of video, per character of audio or per token for LLMs, and serverless GPUs are metered by the second and scale to zero when idle. Failed or rate-limited requests are not charged.

### Is there a free trial?
Yes — new users who sign up with a business email receive $2 in free credits to test models on the platform.

### Can I run my own model or container?
Yes. You can bring your own containers and model weights and run them on the same modular GPU infrastructure that powers the Runware API, billed by the second. Uploaded models and content remain private.

### Does Runware train on my data?
No. Runware states that it does not use your inputs or outputs to train models, and enterprise teams can enable Zero Data Retention so request content is not stored.

### Runware の月間トラフィックと成長トレンドはどうですか？
Runware は現在、月間 40.29万の訪問があり、前月比のトラフィック変動は +8.58万（成長率 +27.1%）です。主要な流入市場はアメリカ合衆国（シェア 27.3%）で、月間 18.98万のダイレクト訪問と月間 — のオーガニック検索訪問を含みます。

### Runware は無料ですか？料金モデルは何ですか？
Runware は有料の料金モデルで運営されています。Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales. 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 Runware 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、Runware の代替ツールトップ5は次のとおりです: 1. fal.ai（月間 309.37万訪問）; 2. Replicate AI（月間 90.4万訪問）; 3. Novita AI（月間 27.14万訪問）; 4. Atlas Cloud（月間 77.7万訪問）; 5. DeepInfra（月間 45.78万訪問）。

### Runware 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？
Runware は AI API, AI画像生成, Text to Image, AIモデルに分類され、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 Stable Diffusion API, 画像生成, 生成AI, AIプラットフォーム, 画像編集, 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 |
| :--- | :--- | :--- | :--- |
| [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-runware) |
| [Replicate AI](https://openaitools.app/ja/tool/replicate-ai) | 904,038 | 有料 | [比較](https://openaitools.app/ja/compare/replicate-ai-vs-runware) |
| [Novita AI](https://openaitools.app/ja/tool/novita-ai) | 271,371 | 有料 | [比較](https://openaitools.app/ja/compare/novita-ai-vs-runware) |
| [Atlas Cloud](https://openaitools.app/ja/tool/atlas-cloud) | 777,031 | 有料 | [比較](https://openaitools.app/ja/compare/atlas-cloud-vs-runware) |
| [DeepInfra](https://openaitools.app/ja/tool/deep-infra) | 457,810 | 有料 | [比較](https://openaitools.app/ja/compare/deep-infra-vs-runware) |
| [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/runware-vs-together-ai) |
| [AI/ML API](https://openaitools.app/ja/tool/ai-ml-api) | 232,946 | Pay-as-you-go credits (free to start); enterprise custom pricing on request | [比較](https://openaitools.app/ja/compare/ai-ml-api-vs-runware) |
| [ModelsLab](https://openaitools.app/ja/tool/modelslab) | 74,376 | フリーミアム、有料 | [比較](https://openaitools.app/ja/compare/modelslab-vs-runware) |
| [RunningHub](https://openaitools.app/ja/tool/runninghub) | 3,105,554 | フリーミアム | [比較](https://openaitools.app/ja/compare/runninghub-vs-runware) |
| [OpenRouter](https://openaitools.app/ja/tool/openrouter-ai) | 19,941,437 | 有料 | [比較](https://openaitools.app/ja/compare/openrouter-ai-vs-runware) |

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出典: https://openaitools.app/ja/tool/runware