Stable Diffusion（Stability AI）每月有 341,872 次造訪，月增率 +1.2%，定價模式為免費增值、需聯絡報價。TypeSafe AI - Jev 每月有 6,148,688 次造訪，成長率 -36.4%，定價模式為付費。
面向圖像、影片、音訊與 3D 的開放生成模型
TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.
| 面向／指標 | | |
|---|---|---|
| 官方網域 | stability.ai | typesafe.ai |
| 定價模式 | 免費增值、需聯絡報價 | 付費 |
| 每月造訪次數 | 34.19萬 (341,872) | 614.87萬 (6,148,688) |
| 月流量變化量 | +3940 (+1.2%) | -351.3萬 (-36.4%) |
| 主要市場與市佔 | 🇺🇸 美國 (20.4%) | 🇺🇸 美國 (26.4%) |
| 每月直接造訪 | 13.44萬 | 314.11萬 |
| 使用者評分 | 4.7 | 4.2 |
| 支援平台 | 網站 | 網站 |
面向圖像、影片、音訊與 3D 的開放生成模型
使用讓 Stable Diffusion 廣為人知的模型系列，為行銷、產品圖與創意專案生成並編輯高品質圖像。
建立並編輯影片，包括面向遊戲與娛樂沉浸式世界的 3D 與 4D 影片模型。
使用 Stable Audio 模型系列製作音樂、音景與音效，並提供基於授權資料訓練的開放權重版本。
透過託管 API 把可用於生產的媒體生成能力整合到自己的產品中，無需自建基礎設施。
TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.
Jev outputs typed decisions that application code can act on directly, rather than prose that must be parsed and interpreted.
Every decision carries an estimate of how confident the model is, so you can set thresholds for autonomous action versus human escalation.
TypeSafe reports Jev at roughly 193x faster and 444x cheaper than LLM-based workflows on comparable System One tasks, with a price of $42 per billion input tokens.
Because confidence estimates expose uncertainty, Jev is designed to avoid hallucination-style failures in automation, enabling zero-hallucination decision paths where confidence is high.
Google 的快速原型開發 IDE 與開發者 API 工作台，用於建構以 Gemini 模型為基礎的多模態應用程式。
免費 / 開源對複雜的生成工作流程提供極致的節點式控制，但相較於簡單的 API，學習曲線較陡峭。
提供明顯更快的推論速度與對開發者友善的無伺服器 API，但缺乏像 Civitai 那樣的原生模型訓練工具。
提供針對開源模型的強大雲端託管與微調功能，不過比起專門的推論引擎，通常延遲會高一些。
透過統一的 API 提供更廣泛的託管開源模型，但缺乏社群分享功能。
免費 / 開源Provides an open-source framework for building agent workflows, but requires manual implementation of calibrated decision-scoring logic.
