特化型クラウド規模のエンジニアリングチーム向け統合オブザーバビリティ・セキュリティ・インシデント対応基盤
#1Code Arena は月間 35,827,928 訪問、前月比成長率 +19.4%、料金体系無料を記録しています。Rerun は月間 54,018 訪問、成長率 -23.7%、料金体系無料を記録しています。

Rerun is an open-source SDK and visualizer for multimodal, multi-rate data, positioned as the data layer for physical AI. Using Python, Rust, or C++ APIs, developers can log robotics, computer vision, and sensor data and review it in a viewer that handles time series and 3D together.
| 項目 / 指標 | ![]() | ![]() |
|---|---|---|
| 公式ドメイン | arena.ai | rerun.io |
| 料金モデル | 無料 | 無料 |
| 月間訪問数 | 3582.79万 (35,827,928) | 5.4万 (54,018) |
| 前月比トラフィック増減 | +583.28万 (+19.4%) |
| -1.68万 (-23.7%) |
| 主要市場とシェア | 🇮🇳 インド (13.1%) | 🇺🇸 アメリカ合衆国 (33.9%) |
|---|
| 月間ダイレクト訪問数 | 2433.99万 | 2.49万 |
|---|
| ユーザー評価 | 4.7 | 4.6 |
|---|
| 対応プラットフォーム | ウェブサイト | ウェブサイト |
|---|

Code Arena is a hands-on playground and leaderboard where you can pit leading AI coding models against each other on real web builds, comparing speed, accuracy, and logic in live side-by-side battles.
Send the same coding prompt to multiple leading models and compare their generated apps and logic side by side.
Watch models construct web apps and websites live, so you can see process and output, not just the final file.
Projects go beyond one-off snippets, testing how well a model structures components, routes, and styles together.
Track which coding models accumulate the most wins over time to identify consistently strong performers.

Rerun is an open-source SDK and visualizer for multimodal, multi-rate data, positioned as the data layer for physical AI. Using Python, Rust, or C++ APIs, developers can log robotics, computer vision, and sensor data and review it in a viewer that handles time series and 3D together.
Log, store, and view images, point clouds, 3D transforms, and time series together in one viewer.
Record multi-rate, multimodal data as column-chunks in rrd files, or convert from other formats.
Run full dataframe or SQL queries over robotics data, down into columns, time ranges, and values.
Add derived columns and evolve schemas without breaking history, on the edge or near the data.
特化型クラウド規模のエンジニアリングチーム向け統合オブザーバビリティ・セキュリティ・インシデント対応基盤
#1無料・オープンソース数百万の公開 SKILL.md エージェントスキルを検索・研究

特化型一つの接続環境で AI モデルとエージェントを追跡・評価・出荷。

無料・オープンソース本番AIのためのエージェント可観測性・評価・継続的改善プラットフォーム

無料・オープンソースLabel Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks.


無料・オープンソースMaxim AI is a platform for evaluating, testing, and monitoring AI applications, and the home of Bifrost, an open-source LLM gateway. It helps teams ship reliable AI features with tracing, evaluation, agent simulation, and production observability.

無料・オープンソースVoxel51 is the data platform for physical AI, built on the open-source FiftyOne library. It helps computer vision and robotics teams search, visualize, curate, annotate, and evaluate multimodal datasets — images, video, 3D scenes, and sensor streams — so they can find where models fail and fix the data behind them.

AI モデルが競い合い、人間の投票が最良のデザイン出力を決めるクラウドソース・アリーナ
コーディングエージェントに本当のデザインセンスを与える Agent Skills
無料・オープンソース数百万の公開 SKILL.md エージェントスキルを検索・研究
無料・オープンソースLabel Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks.
Cursor 向けコミュニティ製プラグイン・ルール・MCP サーバーのハブ
無料・オープンソースMaxim AI is a platform for evaluating, testing, and monitoring AI applications, and the home of Bifrost, an open-source LLM gateway. It helps teams ship reliable AI features with tracing, evaluation, agent simulation, and production observability.
無料・オープンソースVoxel51 is the data platform for physical AI, built on the open-source FiftyOne library. It helps computer vision and robotics teams search, visualize, curate, annotate, and evaluate multimodal datasets — images, video, 3D scenes, and sensor streams — so they can find where models fail and fix the data behind them.