OpenJarvisvsFlowise

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

OpenJarvis

AI Agent Frameworks

Local-first personal AI agents that run with Ollama

Flowise

Automation Platforms

Drag-and-drop LLM flow builder

FeatureOpenJarvisFlowise
CategoryAI Agent FrameworksAutomation Platforms
PricingFree (open-source)Free (open-source) + Cloud
GitHub Stars
5k
More stars
35k
PlatformsmacOS, Linux, Windows, WSL2, DockermacOS, Linux, Windows, Docker
Key Features
  • Local-first personal AI agents
  • Built-in Ollama support
  • Morning briefing preset
  • Deep research across web and local documents
  • Code assistant preset
  • Local engines: Ollama, vLLM, SGLang, llama.cpp
  • Optional cloud engines
  • Energy, cost and latency-aware routing
  • Visual flow builder
  • LangChain integration
  • Chatbot builder
  • Agent flows
  • API endpoints
  • Custom tools
Pros
  • + Strong fit for Ollama-based local agent workflows
  • + Apache-2.0 open-source project
  • + Ships ready-to-run presets instead of only framework primitives
  • + Supports both local engines and optional cloud escalation
  • + Built around privacy, cost, latency and energy as first-class constraints
  • + No-code visual builder
  • + LangChain/LlamaIndex integration
  • + Easy deployment
  • + Good for prototyping
  • + Active community
Cons
  • Young v1.0 project with fast-moving docs and releases
  • Local-first does not mean cloud-free unless configured that way
  • Personal-agent presets may need access to sensitive local files, email or calendar data
  • Efficiency claims are project-reported and should be tested on your own workloads
  • Limited for complex custom logic
  • Can be buggy with some nodes
  • Documentation gaps
  • Less flexible than code
Tags
open-sourcelocal-firstpersonal-aiagentsollamalocal-airesearchpython
open-sourceno-codelangchainchatbotvisual

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