Million은 AI 기반 개발자 도구로, React 웹사이트의 성능을 크게 향상시키기 위해 설계되었습니다. VSCode 확장 프로그램 및 컴파일러로 작동하여 IDE 내에서 느린 코드, 불필요한 재렌더링 및 기타 성능 병목 현상을 자동으로 식별합니다. Million은 실행 가능한 자동 수정 기능을 제공하여 개발자가 몇 달이 아닌 몇 분 만에 애플리케이션을 최대 70%까지 최적화할 수 있도록 돕습니다.
Refact는 오픈 소스이며 자체 호스팅이 가능한 자율 AI 코딩 에이전트입니다. IDE에 통합되어 디지털 트윈 역할을 하며, 코딩 작업을 자동화하고, 컨텍스트 인식 자동 완성 및 채팅을 제공하며, 코드베이스에 적응하여 생산성과 데이터 프라이버시를 극대화합니다.
제품 개요
Million 제품 개요
Million은 AI 기반 개발자 도구로, React 웹사이트의 성능을 크게 향상시키기 위해 설계되었습니다. VSCode 확장 프로그램 및 컴파일러로 작동하여 IDE 내에서 느린 코드, 불필요한 재렌더링 및 기타 성능 병목 현상을 자동으로 식별합니다. Million은 실행 가능한 자동 수정 기능을 제공하여 개발자가 몇 달이 아닌 몇 분 만에 애플리케이션을 최대 70%까지 최적화할 수 있도록 돕습니다.
Refact 제품 개요
Refact는 오픈 소스이며 자체 호스팅이 가능한 자율 AI 코딩 에이전트입니다. IDE에 통합되어 디지털 트윈 역할을 하며, 코딩 작업을 자동화하고, 컨텍스트 인식 자동 완성 및 채팅을 제공하며, 코드베이스에 적응하여 생산성과 데이터 프라이버시를 극대화합니다.
Detailed feature comparison
Million vs Refact monthly traffic
Compare Million and Refact by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Million vs Refact monthly traffic comparison, Million currently shows 22.9K visits and Refact shows 112.8K; Refact has about 4.9 times the visible traffic of Million, an absolute difference of about 89.9K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
Million monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 29.9K 월 방문
- 2026/1: 19K 월 방문
- 2026/2: 19K 월 방문
- 2026/3: 16.8K 월 방문
- 2026/4: 12.8K 월 방문
- 2026/5: 22.9K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 39.53% | 9K |
| 🇮🇳India | 29.75% | 6.8K |
| 🇫🇷France | 14.48% | 3.3K |
| 🇧🇷Brazil | 8.44% | 1.9K |
| 🇲🇾Malaysia | 7.8% | 1.8K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 87.13% | 19.9K |
| 리퍼럴 | 12.87% | 2.9K |
검색 키워드
Refact monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 77.5K 월 방문
- 2026/1: 60.3K 월 방문
- 2026/2: 44.7K 월 방문
- 2026/3: 88.8K 월 방문
- 2026/4: 75.5K 월 방문
- 2026/5: 112.8K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 35.47% | 40K |
| 🇮🇳India | 25.58% | 28.9K |
| 🇳🇬Nigeria | 15.43% | 17.4K |
| 🇮🇩Indonesia | 12.33% | 13.9K |
| 🇬🇧United Kingdom | 11.19% | 12.6K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 79.07% | 89.2K |
| 리퍼럴 | 20.93% | 23.6K |
검색 키워드
Usage comparison
Compare the core capabilities of Million and Refact
Million Core features
Refact Core features
Use cases
Million Use cases
Refact Use cases
Million vs Refact:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Million vs Refact comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Million is primarily listed under “코드 어시스턴트”, while Refact is primarily listed under “코드 어시스턴트”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Product type (Million: Browser extension; Refact: Website); Monthly visits (Million: 22.9K; Refact: 112.8K); Monthly growth (Million: 78.6%; Refact: 49.4%); Favorites (Million: 123; Refact: 99); Website (Million: million.dev; Refact: refact.ai). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Million vs Refact monthly traffic comparison, Million currently shows 22.9K visits and Refact shows 112.8K; Refact has about 4.9 times the visible traffic of Million, an absolute difference of about 89.9K visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Refact first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
Million and Refact currently overlap in shared categories: 코드 어시스턴트 및 디버깅; shared tags: 디버깅 및 개발자 도구. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Million's unique categories/tags are 성능 최적화, 코드 분석, 자바스크립트, 린터, NextJS, 최적화, 리액트 및 타입스크립트; Refact's are 리팩토링, 자동화, AI 에이전트, 코드 어시스턴트, 코드 완성, IDE 플러그인, 젯브레인즈 및 오픈 소스. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
Million has no verified rating, 0 comments, 123 favorites, and 129 likes;Refact has no verified rating, 0 comments, 99 favorites, and 101 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Million first
Put Million on the priority trial list when the task aligns with “코드 어시스턴트” and especially 성능 최적화, 코드 분석, 자바스크립트, 린터, NextJS 및 최적화. This follows recorded positioning and does not imply unlisted capabilities are absent.
Million also currently records: pricing is freemium, product type is browser extension, 22.9K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Refact first
Put Refact on the priority trial list when the task aligns with “코드 어시스턴트” and especially 리팩토링, 자동화, AI 에이전트, 코드 어시스턴트, 코드 완성 및 IDE 플러그인. This follows recorded positioning and does not imply unlisted capabilities are absent.
Refact also currently records: pricing is freemium, product type is website, 112.8K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Million and Refact, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




