특화 강점클라우드 규모 엔지니어링 팀을 위한 통합 옵저버빌리티·보안·인시던트 대응 플랫폼
#1Code Arena는 월간 방문 35,827,928, 전월 대비 성장률 +19.4%, 무료 가격 모델을 기록합니다. Rerun는 월간 방문 54,018, 성장률 -23.7%, 무료 가격 모델을 기록합니다.

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.
| 항목 / 지표 | ![]() | ![]() |
|---|---|---|
| 공식 도메인 | arena.ai | rerun.io |
| 가격 모델 | 무료 | 무료 |
| 월간 방문 수 | 3582.79만 (35,827,928) | 5.4만 (54,018) |
| 전월 대비 트래픽 변화량 | +583.28만 (+19.4%) |
| -1.68만 (-23.7%) |
| 주요 시장 및 점유율 | 🇮🇳 인도 (13.1%) | 🇺🇸 미국 (33.9%) |
|---|
| 월 직접 방문 수 | 2433.99만 | 2.49만 |
|---|
| 사용자 평점 | 4.7 | 4.6 |
|---|
| 지원 플랫폼 | 웹사이트 | 웹사이트 |
|---|

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.
특화 강점클라우드 규모 엔지니어링 팀을 위한 통합 옵저버빌리티·보안·인시던트 대응 플랫폼
#1무료 / 오픈소스수백만 개의 공개 SKILL.md 에이전트 스킬을 검색하고 연구하세요

특화 강점하나의 연결 환경에서 AI 모델과 에이전트를 추적·평가·배포하세요.

무료 / 오픈소스프로덕션 AI를 위한 에이전트 관측성, 평가 및 지속적 개선 플랫폼

무료 / 오픈소스Label 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.


무료 / 오픈소스Maxim 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.

무료 / 오픈소스Voxel51 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 모델이 겨루고 사람의 투표가 최고의 디자인 결과물을 결정하는 크라우드소싱 아레나
코딩 에이전트에 진짜 디자인 감각을 부여하는 Agent Skills
무료 / 오픈소스수백만 개의 공개 SKILL.md 에이전트 스킬을 검색하고 연구하세요
무료 / 오픈소스Label 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.
Cursor를 위한 커뮤니티 플러그인·규칙·MCP 서버 허브
무료 / 오픈소스Maxim 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.
무료 / 오픈소스Voxel51 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.