
專項更強Provides industry-leading proprietary frontier models and enterprise reliability, but completely lacks support for open-weight community models.
forms.app 每月有 987,157 次造訪,月增率 -11.2%,定價模式為免費增值、付費。Together AI 每月有 1,645,930 次造訪,成長率 +64.9%,定價模式為免費增值、付費。
| 面向/指標 | ![]() | |
|---|---|---|
| 官方網域 | forms.app | together.ai |
| 定價模式 | 免費增值、付費 | 免費增值、付費 |
| 每月造訪次數 | 98.72萬 (987,157) | 164.59萬 (1,645,930) |
| 月流量變化量 | -12.4萬 (-11.2%) | +64.77萬 (+64.9%) |
| 主要市場與市佔 | 🇧🇷 巴西 (26.1%) | 🇺🇸 美國 (36.3%) |
| 每月直接造訪 | 59.55萬 | 88.22萬 |
| 使用者評分 | 4.2 | 4.7 |
| 支援平台 | 網站 | 網站 |
幾秒內建立表單、問卷與測驗——免費回覆數量不限
以視覺化方式建立表單、問卷、測驗與投票,並可自訂主題與品牌網域。
描述需求即可讓 AI 草擬完整表單,還能改寫問題文案並自動產生選項。
自動把提交資料送入試算表、CRM 或內部系統,無需手動複製。
涵蓋申請、預約、回饋、人力資源、活動與互動測驗等經審核範本。

Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.

專項更強Provides industry-leading proprietary frontier models and enterprise reliability, but completely lacks support for open-weight community models.

專項更強Restricts API usage strictly to Gemini models, offering free prototyping tiers but lacking open-source model variety.
專項更強Restricts API usage strictly to Gemini models, offering free prototyping tiers but lacking open-source model variety.

專項更強一個 API 串接 1500+ 可上線的生成式媒體模型
除了標準文字 LLM 外,還高度專注於部署自訂機器學習模型與媒體生成管線。
免費 / 開源Unsloth is an open-source toolkit for running and training large language models locally. It provides faster, more memory-efficient fine-tuning, a local chat and agent environment with browser use, image and video generation, and an OpenAI-compatible API your existing tools can connect to.
免費 / 開源Unsloth is an open-source toolkit for running and training large language models locally. It provides faster, more memory-efficient fine-tuning, a local chat and agent environment with browser use, image and video generation, and an OpenAI-compatible API your existing tools can connect to.
專項更強極度重視端到端加密與隱私,犧牲了部分設計便利性來換取高安全性的資料收集。
用一個 API 快速、可預測成本地執行 LLM 與多模態模型