--- title: "magic vs dify" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dtyq-magic-vs-langgenius-dify" tools: ["dtyq-magic", "langgenius-dify"] --- # magic vs dify *GraphCanon updated Sep 20, 2026* ## Verdict Pick magic if magic is an open-source suite combining AI agents with workflow management and collaboration tools like instant messaging; pick dify if dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments. [magic](https://www.magicrew.ai/) reports 5.0k GitHub stars, 561 forks, and 17 open issues, last pushed Aug 12, 2026. [dify](https://dify.ai) has 156k stars, 25k forks, and 1.1k open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [magic's repository](https://github.com/dtyq/magic) and [dify's repository](https://github.com/langgenius/dify). | | [magic](/tools/dtyq-magic.md) | [dify](/tools/langgenius-dify.md) | | --- | --- | --- | | Tagline | All-in-one AI productivity platform | Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace. | | Stars | 5,027 | 156,243 | | Forks | 561 | 24,675 | | Open issues | 17 | 1,103 | | Language | TypeScript | TypeScript | | Adopt for | Magic is an open-source suite combining AI agents with workflow management and collaboration tools like instant messaging. | Dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments. | | Persona | - | - | | Runtime | - | - | | License | Magic Open Source License based on Apache 2.0 with additional restrictions, ensuring modifications are open but retaining copyrights and disclaimers as per the license. | Other | | Categories | AI Agents, Developer Tools | AI Agents, Data & Retrieval, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [magic](/tools/dtyq-magic.md) | [dify](/tools/langgenius-dify.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 33d | 0d | | Open issues (now) | 17 | 1.1k | | Stars delta | +48 (30d) | +4.5k (30d) | | Open issues delta | +3 (30d) | +172 (30d) | | Full report | [trust report](/tools/dtyq-magic/trust.md) | [trust report](/tools/langgenius-dify/trust.md) | ## Decision facts: magic - **Requirements:** Requires Docker - **Adopt for:** Magic is an open-source suite combining AI agents with workflow management and collaboration tools like instant messaging. - **License detail:** Magic Open Source License based on Apache 2.0 with additional restrictions, ensuring modifications are open but retaining copyrights and disclaimers as per the license. ## Decision facts: dify - **Adopt for:** Dify is a platform for creating agentic workflows and RAG pipelines, supporting various AI models and tools, deployable on cloud, VPC, or self-hosted environments. ## Choose when ### Choose magic if… - Requirements: Requires Docker. - Tags unique to magic: agi, gpt, llm, low-code. - When a diverse set of functionalities under one platform is required for managing workflows, automating tasks, and enabling seamless communication among team members. ### Choose dify if… - Tags unique to dify: agentic-ai, agentic-framework, agentic-workflow, automation. - Also covers Data & Retrieval. - When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines. ## When NOT to use magic - When focused exclusively on a specialized aspect of AI development like model training, as Magic offers an all-in-one solution which might add unnecessary complexity. - For users requiring immediate Windows OS compatibility without waiting for upcoming support releases, given that Windows is not currently supported in self-hosted setups. ## When NOT to use dify - If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool. - When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites. - If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions. ## Common questions ### What is the difference between magic and dify? magic: All-in-one AI productivity platform. dify: Build Agentic workflows and RAG pipelines with rich AI model and tool support on one collaborative workspace.. See the comparison table for live GitHub stats and shared categories. ### When should I choose magic over dify? Choose magic over dify when Requirements: Requires Docker; Tags unique to magic: agi, gpt, llm, low-code; When a diverse set of functionalities under one platform is required for managing workflows, automating tasks, and enabling seamless communication among team members. ### When should I choose dify over magic? Choose dify over magic when Tags unique to dify: agentic-ai, agentic-framework, agentic-workflow, automation; Also covers Data & Retrieval; When you need a collaborative workspace that supports rich AI model and tool integration for agentic workflows and RAG pipelines. ### When should I avoid magic? When focused exclusively on a specialized aspect of AI development like model training, as Magic offers an all-in-one solution which might add unnecessary complexity. For users requiring immediate Windows OS compatibility without waiting for upcoming support releases, given that Windows is not currently supported in self-hosted setups. ### When should I avoid dify? If your project does not require agentic workflows or RAG pipelines, and you are looking for a more general-purpose AI development tool. When you need a platform that does not require Docker and Docker Compose for setup, as Dify's quick start guide assumes these prerequisites. If your team prefers a platform with a different licensing model, as Dify uses a modified Apache 2.0 license with additional conditions. ### Is magic or dify more popular on GitHub? dify has more GitHub stars (156,243 vs 5,027). Stars measure visibility, not whether either tool fits your constraints. ### Are magic and dify open source? Yes - both are open-source projects on GitHub (magic: Other, dify: Other). ### Where can I find alternatives to magic or dify? GraphCanon lists graph-backed alternatives at [magic alternatives](/tools/dtyq-magic/alternatives) and [dify alternatives](/tools/langgenius-dify/alternatives) ([magic markdown twin](/tools/dtyq-magic/alternatives.md), [dify markdown twin](/tools/langgenius-dify/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/dtyq-magic-vs-langgenius-dify.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, magic or dify? magic: Steady. dify: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for magic and dify? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [magic trust report](/tools/dtyq-magic/trust); [dify trust report](/tools/langgenius-dify/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dtyq-magic`](/api/graphcanon/graph?tool=dtyq-magic) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_