Devin vs Jules
Devin와 Jules를 워크플로, 가격, 개인정보, 모델 지원, 사용 사례 기준으로 비교합니다.
Details checked Aug 14, 2026
Devin
Choose Devin when the goal is to delegate well-scoped engineering work to autonomous cloud agents and review resulting pull requests, tests, and artifacts later. Choose a local AI IDE or CLI agent when the task requires tight interactive control, cheaper short edits, local model support, or provider-neutral model routing.
Jules
Jules is a strong fit for developers who want to hand off bounded GitHub tasks and review the result later rather than continuously pair with an AI inside their editor. Its asynchronous model, automated PR workflow, scheduled tasks, and CI repair capabilities make it particularly relevant for backlog and maintenance automation, while teams requiring local execution, non-GitHub repositories, or mature enterprise purchasing controls should evaluate alternatives.
핵심 차이
워크플로
Devin is an autonomous AI software engineer for delegating real engineering tasks to cloud and desktop agents that work across repositories, tickets, pull requests, shells, browsers, and team tools.
A Google-built asynchronous coding agent that autonomously executes repository tasks in cloud environments and returns reviewable GitHub changes.
에디터 기반
Standalone
Browser
기능 비교
| 항목 | Devin | Jules |
|---|---|---|
| 주요 워크플로 | Devin is an autonomous AI software engineer for delegating real engineering tasks to cloud and desktop agents that work across repositories, tickets, pull requests, shells, browsers, and team tools. | A Google-built asynchronous coding agent that autonomously executes repository tasks in cloud environments and returns reviewable GitHub changes. |
| 유형 | 자율 코딩 에이전트 | 자율 코딩 에이전트 |
| 에디터 기반 | Standalone | Browser |
| 가격 모델 | Freemium | Freemium |
| 시작 가격 | $0 | $0 |
| 무료 플랜 | 예 | 예 |
| 오픈소스 | 아니요 | 아니요 |
| 로컬 모델 | 아니요 | 아니요 |
| BYOK | 아니요 | 아니요 |
| 플랫폼 | Web app, Devin Cloud, Devin Desktop, Devin CLI, Devin API, GitHub, GitLab, Bitbucket, Linear, Jira, Slack, Microsoft Teams, Dedicated enterprise deployment, VPC-connected enterprise environments | Web, CLI |
| 모델 | SWE 1.6, OpenAI, Claude, Gemini, leading open source models | Gemini 3 Flash, Gemini 3.1 Pro |
| 엔터프라이즈 기능 | Enterprise plan, Dedicated deployment option, Customer-isolated environment, AWS PrivateLink support, IPSec tunnel support, SAML SSO, OIDC SSO, RBAC, IdP group integration, Centralized enterprise admin controls, Teamspace isolation, Dedicated account management, Dedicated account and engineering support, Custom terms, Enterprise billing through Agent Compute Units, GitHub Enterprise Server support through private networking, GitLab and Bitbucket private infrastructure support, Artifactory and Nexus private infrastructure support, Trust Center security documentation | Unknown |
| 적합한 경우 | Engineering teams with large backlogs, Parallel task delegation, Bug reproduction and fixing, Feature implementation drafts, Code migrations, Framework upgrades, Monorepo refactors, Unit test generation, Documentation maintenance, PR review workflows, Internal tool building, Customer engineering support, Teams that want background agents producing reviewable pull requests | Delegating well-scoped GitHub issues, Bug fixes and repository maintenance, Dependency upgrades and migrations, Adding or improving automated tests, Implementing isolated features, Recurring maintenance tasks, Automatically repairing CI failures, Running multiple coding tasks asynchronously |
| 적합하지 않은 경우 | Developers who only need fast autocomplete, Teams that cannot grant agents repository or tool access, Highly sensitive production systems without sandboxing and review gates, Users who need local model execution, Users who want provider-neutral BYOK model routing, Non-technical prompt-to-app builders who do not want to review code, Small tasks where a local IDE assistant or CLI agent is faster and cheaper | Developers who want continuous local pair programming inside an editor, Repositories hosted exclusively outside GitHub, Teams requiring a mature standalone enterprise Jules subscription and centralized Workspace purchasing, Highly sensitive projects that cannot execute source code in cloud environments, Workflows dependent on long-running development servers during environment setup |
사용 사례별 추천
Devin lists more team or enterprise controls.
Devin supports more model/provider options or BYOK-style workflows.
가격 비교
Devin
- Free$0 / month
Light quota to code with agents, limited model availability, unlimited inline edits, and unlimited Tab completions.
- Pro$20 / month
Adds increased quotas, full model availability, access to OpenAI, Claude, and Gemini frontier models, free SWE 1.6 usage, and Devin Cloud.
- Max$200 / month
Higher individual quota for power users, including everything in Pro with significantly more usage.
- Teams$80 + $40/full dev seat / month
Team plan with unlimited team members, collaboration, centralized billing, admin analytics, and priority support.
- EnterpriseCustom
Enterprise plan with custom terms, dedicated account team, SAML/OIDC SSO, centralized admin controls, teamspace isolation, and dedicated deployment options.
Jules
- Jules$0
Free tier with up to 15 tasks per rolling 24 hours and 3 concurrent tasks.
- Jules in Pro$19.99 / month
Included with Google AI Pro; up to 100 daily tasks, 15 concurrent tasks, and higher access to newer Gemini models.
- Jules in UltraFrom $99.99 / month
Included with Google AI Ultra; up to 300 daily tasks, 60 concurrent tasks, and priority access to newer models.
개인정보 및 보안
Devin
Devin can process prompts, repository content, shell output, browser activity, issue or ticket data, pull request context, secrets made available through configured tools, knowledge sources, and integration metadata. Enterprise customers can evaluate dedicated deployment, AWS PrivateLink or IPSec private networking, SAML/OIDC SSO, RBAC, and teamspace isolation. Teams should scope permissions narrowly, separate production credentials from agent environments, review generated changes before merge, and avoid giving cloud agents unnecessary access to sensitive systems or data.
Jules
Google states that Jules does not use private repository content to train models. Tasks execute in Google-hosted cloud virtual machines with internet access, so repository permissions should be scoped carefully and secrets should not be committed to source control.
Devin를 선택하기 좋은 경우
- Engineering teams with large backlogs
- Parallel task delegation
- Bug reproduction and fixing
- Feature implementation drafts
- Code migrations
Jules를 선택하기 좋은 경우
- Delegating well-scoped GitHub issues
- Bug fixes and repository maintenance
- Dependency upgrades and migrations
- Adding or improving automated tests
- Implementing isolated features
Devin를 피하는 것이 좋은 경우
- Developers who only need fast autocomplete
- Teams that cannot grant agents repository or tool access
- Highly sensitive production systems without sandboxing and review gates
- Users who need local model execution
- Users who want provider-neutral BYOK model routing
Jules를 피하는 것이 좋은 경우
- Developers who want continuous local pair programming inside an editor
- Repositories hosted exclusively outside GitHub
- Teams requiring a mature standalone enterprise Jules subscription and centralized Workspace purchasing
- Highly sensitive projects that cannot execute source code in cloud environments
- Workflows dependent on long-running development servers during environment setup