Multica vs Dify
Two of the top agent platforms, side by side: score, setup, license, activity and what each review found.
Multica
Issue board where AI coding agents take assignments like teammates
Dify
Visual LLM app platform with workflows, RAG pipeline, agents and APIs
| What we compare | Multica | Dify |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 69, popular | 93, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 86, healthy | 93, healthy |
| Easy to run | 50, easy | 33, some setup |
| Agent-ready | 70, partly | 45, minimal |
| Facts from GitHub and the README | ||
| Stars | 52.6k | 158.2k |
| License | custom license (read the license) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Sep 2026 |
| Language | Go | Not stated |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
Multica
Multica is a workspace where issues are assigned to AI coding agents, which run through locally installed agent CLIs such as Claude Code, Codex, Cursor and Copilot (26 listed). A daemon on your own machine executes the work next to your code and reports progress back to the issue, which ends in review rather than main. The backend is Go with PostgreSQL 17, and clients cover web, Electron desktop and an Expo mobile app.
Who it is for: Teams coordinating several coding agents on their own machines and Git host
Strengths
- Drives 26 existing agent CLIs, so no model or API lock-in
- Execution log replays every tool call, command and error per run
- Daemon runs on your own machine, so code stays there
- Self-host via Docker Compose or Helm; works with GitHub, GitLab, Gitea, Forgejo
Weaknesses
- Does not ship agents; each runtime needs a CLI installed and signed in
- Custom Multica License (Apache 2.0 plus conditions on hosting, embedding, branding)
- Requires Docker, a Go backend and PostgreSQL 17 to self-host
- iOS app builds from source only; DingTalk, WeCom, Telegram are community-maintained
- no GPU
- Docker + Compose
- Needs PostgreSQL 17, Docker, agent CLI (Claude Code, Codex, etc.)
- Models: Claude Code, OpenAI Codex, Cursor Agent, GitHub Copilot CLI, OpenCode
Dify
Dify is an LLM app platform started with Docker Compose (dashboard on port 80) that needs 2 CPU cores and 4 GiB RAM. One canvas covers visual workflows, a prompt IDE, a RAG pipeline that ingests PDFs and PPTs, sandboxed agents using Marketplace tools, MCP servers or your own APIs, plus LLMOps tracing via Opik, Langfuse or Arize Phoenix. Hundreds of models work, including OpenAI-compatible endpoints.
Who it is for: Product teams building LLM apps and RAG workflows without heavy code
Strengths
- Workflow, RAG, agents, prompt IDE and model management in one canvas
- Hundreds of models: GPT, Mistral, Llama3 and any OpenAI-compatible API
- Observability through Opik, Langfuse and Arize Phoenix
- Every feature is exposed through an API (backend-as-a-service)
Weaknesses
- Dify Open Source License adds conditions on top of Apache 2.0
- SSO, RBAC and support SLAs are reserved for Dify Enterprise
- Minimum 2 CPU cores and 4 GiB RAM for the Compose stack
- Dashboard binds to port 80 by default
- RAM ≥ 4 GB
- no GPU
- Docker + Compose
- Models: OpenAI GPT, Mistral, Llama 3, OpenAI-compatible APIs, dozens of inference providers
- port 80