Lovable 记录了 31,052,090 月访问量,月度环比增长为 +3.8%,定价为免费增值。TypeSafe AI - Jev 记录了 6,148,688 月访问量,增长率为 -36.4%,定价为付费。

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.
| 维度 / 指标 | ![]() | |
|---|---|---|
| 官方域名 | lovable.dev | typesafe.ai |
| 定价模式 | 免费增值 | 付费 |
| 月访问量 | 3105.21万 (31,052,090) | 614.87万 (6,148,688) |
| 月度环比流量变化 | +115万 (+3.8%) | -351.3万 (-36.4%) |
| 主要市场与份额 | 🇺🇸 美国 (20.6%) | 🇺🇸 美国 (26.4%) |
| 直接访问 / 月 | 2026.56万 | 314.11万 |
| 用户评分 | 4.8 | 4.2 |
| 支持的平台 | 网站 | 网站 |
用对话描述想法,Lovable 把它变成可运行的网站或应用
用日常语言描述功能,构建器便会创建或修改全栈 Web 应用的界面、逻辑与结构。
生成前端、后端函数与数据库支撑的功能,而不只是静态效果图,让成果真正能跑起来。
把项目部署到可分享的线上地址,准备正式上线时再绑定自定义域名。
将应用接入外部 API 与服务,并在产品内直接加入对话、搜索或内容生成等 AI 能力。

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 的快速原型开发 IDE 与开发者 API 工作台,用于构建基于 Gemini 模型的多模态应用。

专项更强Focuses heavily on high-end visual design and marketing sites with AI generation, but less on complex backends.
专项更强Focuses heavily on high-end visual design and marketing sites with AI generation, but less on complex backends.