AutoGPT vs dify
The two are close in size: 187.1k stars for AutoGPT, 154.5k for dify. Over the days we have tracked them AutoGPT moved +0.8% and dify +3.6%, so dify is growing faster right now.
AutoGPT leads on context depth. dify does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Provides both a managed, no-API-key hosted platform and an open-source self-hostable agent runtime with a visual builder and marketplace.
- Stars
- 187.1k
- Tracked growth
- +0.8%
- Maturity
- ●●●●●
- Last commit
- 17m ago
- Language
- Python
- License
- NOASSERTION
- Cost to run
- Paid hosted service; self-hosted uses your infrastructure and model-provider costs
Integrated low-code workspace combining visual AI workflows, RAG pipelines, agent builders, and broad multi-provider model support that can be self-hosted.
- Stars
- 154.5k
- Tracked growth
- +3.6%
- Maturity
- ●●●●●
- Last commit
- 27m ago
- Language
- TypeScript
- License
- NOASSERTION
- Cost to run
- Free cloud sandbox (200 GPT-4 calls); self-hosted on your infra.
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | AutoGPT | dify |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Workspace-level access | ●●●●● Diff/file only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● None mentioned | ●●●●● None mentioned |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Visual builder & marketplace | ●●●●● Prompt IDE & tools |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable / local |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring your own key | ●●●●● Bring-your-key / any |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-click hosted | ●●●●● Docker Compose quickstart |
Which one to pick
Pick AutoGPT if…
Flexible deployment — use the managed platform for instant agents or self-host to retain control over infrastructure, data, and model keys.
- Context depth: Workspace-level access (3/5 against 1/5)
Pick dify if…
Easy deployment — run a full-featured, visual LLM app and agent platform locally or in your VPC using Docker Compose (or use Dify Cloud for a sandbox with free GPT‑4 calls).
What people want from each one
Significant-Gravitas/AutoGPT
Hacker News: AI Report #4: AutoGPT And Open-source lags behind Part 2 drew 60 points and 36 comments.
langgenius/dify
Hacker News: Dify, a visual workflow to build/test LLM applications drew 185 points and 38 comments.
Questions people ask
Is AutoGPT better than dify?
AutoGPT leads on context depth. dify does not take any axis by a clear margin. AutoGPT is worth picking when flexible deployment — use the managed platform for instant agents or self-host to retain control over infrastructure, data, and model keys.
Which of AutoGPT and dify keeps my code private?
AutoGPT: Self-hostable (4/5). dify: Self-hostable / local (5/5).
What does each one cost to run?
AutoGPT: Paid hosted service; self-hosted uses your infrastructure and model-provider costs. dify: Free cloud sandbox (200 GPT-4 calls); self-hosted on your infra..
Full profiles: Significant-Gravitas/AutoGPT and langgenius/dify. Everything else in Low-code builders.