# Models.dev vs SuperAnnotate Models.dev 每月有 200,451 次造訪，月增率 -3.9%，定價模式為免費。SuperAnnotate 每月有 386,034 次造訪，成長率 +37.4%，定價模式為免費試用、需聯絡報價。 | 指標 | [Models.dev](https://openaitools.app/tw/tool/models-dev) | [SuperAnnotate](https://openaitools.app/tw/tool/super-annotate) | | :--- | :--- | :--- | | 網站網址 | https://models.dev | https://www.superannotate.com | | 分類 | AI 模型, AI API, 開源 AI 模型, AI 工具目錄 | AI Workflow, AI 開發者工具, AI 專案管理 | | 定價模式 | 免費 | 免費試用、需聯絡報價 | | 每月造訪次數 | 200,451 | 386,034 | | 月成長率 | -3.9% | +37.4% | | 主要市場 | 中國 | 美國 | | 直接造訪 | 136,316 | 248,258 | | 評論分數 | 4.4 | 4.6 | | 收藏數 | 0 | 0 | | 支援平台 | 網站 | 網站 | ## Models.dev Models.dev 要回答一個非常實際的問題：該用哪個模型，成本是多少？網站為每個項目設定形如 provider/model 的規範識別碼，因此同一模型在不同供應商下的版本可以直接比較。表格欄位包含上下文視窗、最大輸出、是否支援輸入與輸出、推理、工具呼叫、結構化輸出、溫度控制、開放或閉源權重、每百萬 token 價格，以及發布與更新日期。 由於模型發布節奏很快，該目錄以保持最新為目標，提供可排序與可搜尋的表格，能依實驗室或供應商瀏覽並篩選關鍵條件。項目同時涵蓋閉源旗艦模型與開放權重模型，既能用於成本規劃，也能用於能力調研。 專案開源且免費，定位為可被程式化取用的資料源。開發者可透過 JSON API 或型別安全 SDK 把目錄接入自家工具，因此很適合作為儀表板、路由邏輯或內部成本計算器的後端，而不只是瀏覽用的參考頁。 **價格與方案:** Models.dev 免費且開源。它本身是參考資料庫，所列價格是模型供應商收取的每百萬 token 費率，而非使用本站的費用。 - **規範模型識別碼:** 每個模型採用統一的 provider/model 格式，方便跨供應商直接對比同一模型。 - **規格對比:** 並排查看上下文視窗、輸出上限、推理、工具呼叫、結構化輸出與溫度支援。 - **價格透明:** 列出每百萬 token 的輸入輸出價格，並標註發布與更新日期。 - **開源與閉源兼顧:** 在一個可排序目錄中同時涵蓋閉源旗艦 API 與各實驗室的開放權重模型。 - **面向開發者:** 可透過 JSON API 或型別安全 SDK 取得目錄，用於自建工具與儀表板。 **優勢:** 免費開源，無需註冊帳號; 統一的規範識別碼讓跨供應商對比更可靠; 在同一張可排序表格中呈現價格、上限與能力; 提供 JSON API 與型別安全 SDK，便於程式化使用 **限制:** 它是參考目錄，並非推論或託管服務; 資料品質取決於社群與維護者能否跟上發布節奏; 介面面向開發者，對非技術使用者幾乎沒有引導 [Profile (Markdown)](https://openaitools.app/tw/tool/models-dev.md) ## SuperAnnotate SuperAnnotate is an AI data platform that combines a collaborative multimodal annotation editor, an expert data-operations team, and the orchestration layer needed to move curated datasets into training, evaluation, and production pipelines. It is aimed at teams building computer vision, NLP, audio, and generative AI systems who need reliable, high-quality ground truth at scale. **價格與方案:** SuperAnnotate publishes three main tiers: Starter, Pro, and Enterprise. Starter is described as an entry point for small projects, Pro targets scaled AI and MLOps workloads and is sold via a demo request, and Enterprise is quoted through sales for well-established, recurring, high-volume programs. Published plan comparison highlights compute orchestration allowances of roughly 1K compute hours on Starter, 2.5K on Pro, and 10K on Enterprise, with SSO, dedicated Slack channels, a customer success manager, a solutions engineer, and AI DataOps consulting reserved for higher tiers. Exact prices are not listed publicly, so you should contact the vendor for a quote. - **Customizable multimodal editor:** One configurable annotation surface for image, video, text, and audio projects, so multimodal datasets can be labeled without switching tools. - **Data curation and exploration:** Search, filter, and inspect datasets to find the examples that will most improve a model, then route them into targeted annotation or review queues. - **Analytics and insights:** Dashboards for annotation volume, reviewer agreement, and project progress, plus advanced analytics on upper tiers for program-level reporting. - **Compute orchestration:** Metered orchestration capacity for running annotation, evaluation, and data-processing workloads, scaled by plan from roughly 1K to 10K compute hours. - **Managed Data Operations:** Optional access to SuperAnnotate's own annotation experts and AI DataOps consultants to run large or specialized data programs end to end. **優勢:** Unified editor removes the need to maintain separate tools per modality; Rich project management and quality analytics suited to large distributed teams; Enterprise-grade governance features such as SSO and dedicated support channels; Managed data-operations services let you outsource complex or high-volume programs **限制:** No public list price, so budgeting requires a sales conversation; Advanced analytics, SSO, and dedicated support are locked to higher tiers; The breadth of features can be heavy for individuals or very small teams; Compute orchestration capacity is metered and may require planning for large jobs [Profile (Markdown)](https://openaitools.app/tw/tool/super-annotate.md) ## 常見問題 ### Models.dev 與 SuperAnnotate 的每月流量相比如何？ Models.dev 每月有 200,451 次造訪，而 SuperAnnotate 有 386,034。流量估算反映受眾規模，並非產品品質。 ### 兩者的成長率相比如何？ Models.dev 的月增率為 -3.9%；SuperAnnotate 為 +37.4%。 ### 價格相比如何？ Models.dev：免費。Models.dev 免費且開源。它本身是參考資料庫，所列價格是模型供應商收取的每百萬 token 費率，而非使用本站的費用。 SuperAnnotate：免費試用、需聯絡報價。SuperAnnotate publishes three main tiers: Starter, Pro, and Enterprise. Starter is described as an entry point for small projects, Pro targets scaled AI and MLOps workloads and is sold via a demo request, and Enterprise is quoted through sales for well-established, recurring, high-volume programs. Published plan comparison highlights compute orchestration allowances of roughly 1K compute hours on Starter, 2.5K on Pro, and 10K on Enterprise, with SSO, dedicated Slack channels, a customer success manager, a solutions engineer, and AI DataOps consulting reserved for higher tiers. Exact prices are not listed publicly, so you should contact the vendor for a quote. ## 替代方案 | # | 工具名稱 | 每月造訪次數 | 月成長率 | 定價模式 | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Labelbox](https://openaitools.app/tw/tool/labelbox) | 762,803 | -22.8% | 需聯絡報價 | 強大的企業級資料標註與代理自動化，但具備不同的協作介面與定價結構。 | [.md](https://openaitools.app/tw/tool/labelbox.md) | | 2 | [Appen](https://openaitools.app/tw/tool/appen-com) | 665,840 | +0.2% | 需聯絡報價 | Extensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility. | [.md](https://openaitools.app/tw/tool/appen-com.md) | | 3 | [Weights & Biases（CoreWeave Forge）](https://openaitools.app/tw/tool/prompts) | 315,624 | -80.2% | 免費增值、需聯絡報價、免費 | Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments. | [.md](https://openaitools.app/tw/tool/prompts.md) | | 4 | [Encord](https://openaitools.app/tw/tool/encord-com) | 244,204 | +9.4% | 需聯絡報價 | 具備優秀的電腦視覺多模態資料基礎設施，但缺少 SuperAnnotate 的部分更廣泛企業專案管理工具。 | [.md](https://openaitools.app/tw/tool/encord-com.md) | | 5 | [Stork](https://openaitools.app/tw/tool/stork) | 201,544 | +2.3% | 免費 | Includes model pricing trackers and developer news alongside tools directories, but less focused on raw API specs. | [.md](https://openaitools.app/tw/tool/stork.md) | | 6 | [Defined.ai](https://openaitools.app/tw/tool/definedcrowd-com) | 146,251 | -21% | 需聯絡報價 | Strong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling. | [.md](https://openaitools.app/tw/tool/definedcrowd-com.md) | | 7 | [Label Studio](https://openaitools.app/tw/tool/label-studio) | 137,199 | -16.1% | 需聯絡報價、免費 | 強大的開源資料標註並支援深度自訂，但需要自行架構且缺乏開箱即用的託管企業工作流程。 | [.md](https://openaitools.app/tw/tool/label-studio.md) | | 8 | [Voxel51](https://openaitools.app/tw/tool/voxel51-com) | 117,715 | -8.2% | 需聯絡報價 | 具備出色的電腦視覺視覺化資料集搜尋與策展功能，但較不專注於手動文字與多模態標註。 | [.md](https://openaitools.app/tw/tool/voxel51-com.md) | | 9 | [InfraBase.ai](https://openaitools.app/tw/tool/infrabase-ai) | 39,072 | -13.6% | 免費 | Catalogues and compares AI infrastructure tools and services across categories, but lacks deep per-token pricing tables. | [.md](https://openaitools.app/tw/tool/infrabase-ai.md) | | 10 | [BasicAI Cloud](https://openaitools.app/tw/tool/basicai-cloud) | 21,670 | -13.1% | Freemium, Enterprise Quote | 提供高效的訓練資料標註與託管服務，但生態系統比 SuperAnnotate 小。 | [.md](https://openaitools.app/tw/tool/basicai-cloud.md) | --- 來源：https://openaitools.app/tw/compare/models-dev-vs-super-annotate More Markdown: [分類](https://openaitools.app/tw/categories.md) · [流量排名](https://openaitools.app/tw/rankings.md) · [llms.txt](https://openaitools.app/tw/llms.txt)