These three sit at different layers of a private or local AI stack rather than being pure substitutes: Ollama is the free, lightweight runtime that downloads…
Freemium · From Free (desktop/self-hosted); Cloud from $50/month
Best for: Individuals and small teams who want a ready-made, privacy-first app for chatting with their own documents and running agents without building anything from scratch
Freemium (free open-source self-hosting plus a paid Flowise Cloud with free, Starter, Pro, and Enterprise tiers) · From Free (self-hosted or Cloud Free plan); paid Cloud plans start at $35/month
Best for: Developers and technical teams who want a visual, drag-and-drop canvas to design and deploy custom RAG pipelines and multi-agent workflows as APIs
Best for: Anyone who just needs a free, lightweight way to download and run open-weight LLMs locally via CLI or REST API, often as the backend model source for other tools
At a Glance
AnythingLLM
Flowise
Ollama
Primary category
AI
AI
AI
Rating
Not documented
Not documented
Not documented
Pricing model
Freemium
Freemium (free open-source self-hosting plus a paid Flowise Cloud with free, Starter, Pro, and Enterprise tiers)
Freemium
Starting price
Free (desktop/self-hosted); Cloud from $50/month
Free (self-hosted or Cloud Free plan); paid Cloud plans start at $35/month
Free
Free plan
Yes
Yes
Yes
Free trial
Not documented
Not documented
Not documented
Platforms
Mac, Windows
Web
Mac, Windows
Team collaboration
Not documented
Not documented
Not documented
AI features
Yes
Yes
Yes
Public API
Yes
Yes
Yes
Standout Differences
Ollama is the model engine, not a full application
Ollama wraps llama.cpp behind a simple CLI and REST API for pulling and running open-weight models like Llama, Qwen, and Mistral; it does not include a document-chat interface or visual workflow builder the way AnythingLLM and Flowise do.
Ollama
AnythingLLM ships a ready-made private chat app
AnythingLLM is purpose-built for chatting with PDFs, Word files, CSVs, and codebases entirely on-device, with AI agents layered on top, so it needs the least assembly to get a usable private assistant running.
AnythingLLM
Flowise trades turnkey simplicity for visual workflow control
Flowise's drag-and-drop Chatflows and Agentflows, plus over 100 model and vector store integrations, let teams design custom RAG and multi-agent logic visually rather than accepting a fixed app structure.
Flowise
All three are free to self-host, with different paid cloud tiers
AnythingLLM, Flowise, and Ollama each offer a free open-source or local core, with optional paid cloud plans ranging from Ollama Cloud at $20 to $100 per month, to AnythingLLM Cloud at $50 to $99 per month, to Flowise Cloud at $35 to $65 per month.
AnythingLLM, Flowise, Ollama
AnythingLLM and Flowise both expose developer APIs for embedding
Both tools can be integrated into other applications through a built-in developer API, while Ollama's REST API is aimed at serving model inference rather than embedding a finished chat or agent experience.
AnythingLLM, Flowise
Feature-by-Feature
Core Capability
Feature
AnythingLLM
Flowise
Ollama
Document chat or RAG out of the box
Available
Available
Unavailable
Visual drag-and-drop workflow builder
Unavailable
Available
Unavailable
Multi-agent orchestration
Available
Available
Not documented
One-command open-weight model library
Not documented
Not documented
Available
Deployment and Integration
Feature
AnythingLLM
Flowise
Ollama
Local or offline operation
Available
Available
Available
Built-in developer API
Available
Available
Available
Pricing Model
Feature
AnythingLLM
Flowise
Ollama
Free self-hosted or local core
Available
Available
Available
Paid managed cloud tier
Available
Available
Available
Pricing Compared
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
AnythingLLM
Desktop / Self-Hosted — Free N/A
Cloud Basic — $50/month Monthly
Cloud Pro — $99/month Monthly
Enterprise — Custom Custom
Flowise
Free — Free N/A
Starter — $35/month monthly
Pro — $65/month monthly
Enterprise — Custom annual (negotiated)
Open Source (Self-Hosted) — Free N/A
Ollama
Local (self-hosted) — Free n/a
Ollama Cloud Free — $0 monthly
Ollama Cloud Pro — $20/month ($200/year) monthly or annual
Ollama Cloud Max — $100/month monthly
Pros & Cons
AnythingLLM
Pros
Strong privacy and local-first design with no forced data sharing
Free desktop app requiring no account
Flexible support for multiple LLM providers, including local models
Open source under the MIT license
Cons
Cloud plans are priced per user-tier rather than pure usage-based pricing
Enterprise pricing isn't publicly listed and requires contacting sales
Self-hosting via Docker requires some technical setup
Flowise
Pros
Free and open source under the permissive Apache 2.0 license, with no-cost self-hosting available on any infrastructure.
Visual, drag-and-drop interface lowers the barrier to building RAG chatbots and multi-agent systems compared to writing LangChain code by hand.
Broad integration coverage across more than 100 LLMs, embedding models, and vector databases.
Supports both simple chatbots and more complex, coordinated multi-agent workflows with human-in-the-loop review.
Cons
Flowise Cloud subscription prices do not include LLM token usage, so real production costs can run well above the listed plan price once model API bills are added.
Self-hosting requires comfort with Docker and cloud infrastructure, which adds setup and maintenance overhead for non-technical teams.
Enterprise pricing is not published and must be negotiated directly with sales, making budgeting harder for larger deployments.
As a very small, now Workday-owned team historically, long-term open-source roadmap priorities may increasingly reflect Workday's enterprise product needs rather than the broader community's.
Ollama
Pros
Core local runtime is completely free and open source with no per-token cost
Runs entirely offline, keeping data on the user's own device for privacy-sensitive use cases
Broad model library with one-command installation of popular open-weight models
Cross-platform support across macOS, Windows, Linux, and Docker
Large, active developer community with tens of thousands of integrations
Cons
Local model performance is limited by the user's own hardware, especially without a capable GPU
Cloud tier pricing (Pro at $20/month, Max at $100/month) adds cost for users needing more concurrency or larger models
AMD GPU acceleration is Linux-only as of 2026, limiting Windows AMD users to CPU inference
Managing local models and disk space can become cumbersome as model libraries grow
As a young, fast-growing company (founded 2023), product and pricing details are still evolving
Use Cases
Choose AnythingLLM: Individuals and small teams who want a ready-made, privacy-first app for chatting with their own documents and running agents without building anything from scratch
Choose Flowise: Developers and technical teams who want a visual, drag-and-drop canvas to design and deploy custom RAG pipelines and multi-agent workflows as APIs
Choose Ollama: Anyone who just needs a free, lightweight way to download and run open-weight LLMs locally via CLI or REST API, often as the backend model source for other tools
AnythingLLM
Private document Q&A — Chat with personal or company documents without sending data to a third-party cloud AI service.
Building AI agents on proprietary data — Create AI agents that operate over your own documents and knowledge base.
On-premise enterprise AI deployment — Deploy a self-hosted AI chat and agent platform within enterprise infrastructure.
Flowise
Rapid RAG chatbot prototyping — Developers connect a document loader, vector store, and chat model on the Flowise canvas to stand up a retrieval-augmented chatbot over internal knowledge bases in minutes rather than writing custom LangChain code.
Internal enterprise AI assistants — Product and IT teams use Flowise's Chatflows and Agentflows to build customer-support bots, internal knowledge assistants, and multi-step business process agents that plug into existing enterprise data sources.
Governed, large-scale agent deployment — Large organizations use Flowise's Enterprise tier, with SSO/SAML, RBAC, audit logging, and on-premises deployment, to design, launch, and govern AI agents at scale across regulated business units.
Ollama
Private, offline AI development — Developers run models locally to prototype AI features without sending data to third-party APIs.
Privacy-sensitive enterprise deployment — Organizations with strict data handling requirements run LLMs on internal infrastructure using Ollama instead of external APIs.
AI experimentation and learning — Hobbyists and students experiment with different open-weight models on personal hardware to learn about LLM behavior.
Frequently Asked Questions
Do I need Ollama if I already use AnythingLLM or Flowise?
Not necessarily, since both AnythingLLM and Flowise can connect to cloud LLM providers like OpenAI or Azure. But many users pair them with Ollama so model inference runs locally: Ollama serves the model and AnythingLLM or Flowise provides the document-chat or workflow layer on top.
Which is easiest for a non-developer to start with?
AnythingLLM is the closest to a ready-to-use app; the free desktop version requires no account and works out of the box for chatting with documents, while Flowise and Ollama both expect more comfort with building flows or using a CLI.
Which tool is best for building a custom multi-agent workflow?
Flowise is the strongest fit here, with its visual Agentflows for coordinating multi-step, multi-agent systems and over 100 integrations across LLM providers and vector stores. AnythingLLM also supports agents but with less visual workflow control, and Ollama has no orchestration layer of its own.
Are all three free to self-host?
Yes. AnythingLLM's desktop and self-hosted versions are free and MIT licensed, Flowise's core is free under Apache 2.0 and self-hostable via Docker, and Ollama's local runtime is free and open source with no per-token cost.
Can these tools run completely offline?
Yes, all three support local or offline operation: AnythingLLM's desktop app can run entirely on-device, Flowise can be self-hosted on infrastructure you control, and Ollama's core purpose is running models locally without sending data to a third-party API.