Dify vs Ollama: which one to choose in 2026?
Both are open source alternatives to OpenAI API. We compare license, tech stack and features to help you decide which fits your team best.
| Dify | Ollama | |
|---|---|---|
| Category | Artificial Intelligence | Artificial Intelligence |
| License | Apache-2.0 | MIT |
| GitHub stars | ~54k | ~99k |
| Tech stack | Python, Next.js, PostgreSQL | Go, Llama.cpp |
| Replaces | OpenAI API | OpenAI API |
Ollama has more GitHub stars, which usually indicates a larger community (not necessarily that it's the best option for your use case).
Dify
Platform for building AI apps with a visual editor and observability.
ℹ️ 40GB is the project's official recommendation for a production deployment (covers Postgres, Redis and the rest of the stack). No GPU of its own required — it only helps if you connect a local embeddings/inference runtime.
Pros
- Cuts down a lot of the code needed to ship an AI product
Things to consider
- Full production stack has several services (Weaviate/Redis)
Ollama
Run open source LLMs locally, an alternative to the OpenAI API.
ℹ️ CPU-only is viable for models ≤7B (needs ~8GB of free RAM). For 13B+ models or fast inference, a dedicated GPU with at least 8-12GB VRAM is recommended.
Pros
- Your data never leaves your server
Things to consider
- Quality depends on the model and hardware available
Key features
Dify
- Visual editor for AI agents and flows
- Observability and logs for every conversation
- Multi-model: OpenAI, Anthropic, local
Ollama
- Download models with a single command
- API compatible with multiple clients
- GPU and CPU support
Already know which one you prefer?
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