Dify vs Ollama

Bottom line

Dify has a free plan plus paid upgrades, while Ollama is free. Ollama is open source and Dify is not.

Which one should you try?

Dify

Freemium

Best for Teams building RAG, chatbot or agent apps with a visual builder

Visit Dify See full review

Ollama

Free

Best for Developers who want a local model API without managing model files by hand

Visit Ollama See full review

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Dify

LLM app platform with visual workflows, RAG, agents and app APIs. Free Sandbox and self-hosted Community edition.

Ollama

Ollama downloads open models and runs them locally behind a command line and API, with optional cloud-hosted models. We ran it on a 3-core CPU server and measured startup, memory and speed.

Attribute	Dify	Ollama
Pricing	Freemium	Free
Price	Free Sandbox; Professional $590/workspace/year; Team $1,590/workspace/year (annual billing)	Free (MIT). Optional Ollama Cloud from $20/mo
Pricing checked	Oct 17, 2026	Apr 10, 2026
Free trial	Not stated	Not stated
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	Yes	Yes
Platforms	Dify Cloud (web); self-hosted with Docker Compose (min. 2 CPU cores, 4 GiB RAM)	macOS, Windows, Linux, Docker
Released	—	2023-06
Pros	Workflows, RAG, agents and logging in one platform, with an API for every app. Connects to many model providers, including any OpenAI-compatible endpoint. Free self-hosted Community edition via Docker Compose, alongside hosted Dify Cloud.	Pulls and runs a model with one command and serves it over a local API. Quick cold start in our test: about 8 seconds from server start to first answer. OLLAMA_NO_CLOUD=1 turns off its cloud models and web search for local-only use. Generated text faster than LM Studio on the same model and cores, by up to 1.38x with short prompts.
Cons	The modified Apache 2.0 license requires authorization for multi-tenant services and bars removing frontend branding. Multiple workspaces and commercial license authorization are Enterprise features. Model API usage is billed by providers once included cloud credits run out.	Ignores a container's CPU limit: it started 8 threads on 3 cores, and generation was 3.3 to 11.9 times slower until we set num_thread to 3. Caps context at the model's trained length (32,768 tokens for our model) even when you ask for more, so check what you actually get. The largest Docker image of the runtimes we tested: 9.37 GB, against 1.21 GB for llama.cpp.

Made up your mind?

Dify

Freemium

Best for Teams building RAG, chatbot or agent apps with a visual builder

Visit Dify See full review

Ollama

Free

Best for Developers who want a local model API without managing model files by hand

Visit Ollama See full review

Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.

Dify vs Ollama

Which one should you try?

Dify

Ollama

Dify

Ollama

Made up your mind?

Dify

Ollama

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