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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Jan.ai logo
Jan.ai
✓ verifiedFree

Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.

378K visits/mo609 saves
HEROZ logo
HEROZ
✓ verifiedPaid

A Japanese AI firm that grew from shogi-AI research into industry ML solutions and a generative-AI platform, HEROZ ASK.

1.9M visits/mo
Google Antigravity logo
Google Antigravity
✓ verifiedFree

Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.

22M visits/mo18K saves
Dify.ai logo
Dify.ai
✓ verifiedFreemium

Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.

1.1M visits/mo
MuleRun logo
MuleRun
✓ verifiedFreemium

Always-on cloud AI agent that runs multi-step workflows and monitoring on a dedicated 24/7 VM to automate business tasks.

908K visits/mo
Pricing

No public pricing

No public pricing

No public pricing

Sandbox: Free (200 message credits)
Professional: $590/workspace/year
Team: $1,590/workspace/year
Free: $0 (200 daily bonus credits, 10 tasks)
Plus: $16/mo (2,000 credits/mo)
Super: $32/mo (4,500 credits/mo)
Pro: $160/mo (23,000 credits/mo)
Core features
  • Run open-source LLMs locally
  • Connect to online models (OpenAI, Claude, Gemini)
  • Private, offline-capable AI chat
  • Open source and self-hostable
  • Model library via Hugging Face
  • Cross-platform desktop app
  • Deep-learning and machine-learning core technology
  • HEROZ ASK generative-AI platform
  • BtoB and BtoC AI solutions
  • BLOOMWORKS product
  • Industry AI deployment case studies
  • Agent-first IDE experience
  • Autonomous planning and code execution
  • Integrated editor, terminal and browser control
  • Powered by Google's Gemini models
  • High-level developer supervision
  • Visual workflow studio for agents
  • RAG knowledge pipelines
  • Agent runtime with tools and memory
  • Marketplace of models and plugins
  • Publish as app, API or MCP tool
  • Logging, analytics and monitoring
  • Always-on agent on a dedicated 24/7 VM
  • Multi-step task automation (docs, PPT, video, research)
  • Proactive monitoring with alerts and actions
  • Shared/self-improving agent knowledge network
  • Page deployment and drive storage
Use cases
  • Private local AI chat
  • Using multiple models in one app
  • Avoiding cloud data sharing
  • Experimenting with open models
  • Deploying generative AI in enterprises
  • Applying ML to industry-specific problems
  • AI-driven business transformation (DX)
  • Building apps with AI agents
  • Automating multi-step coding tasks
  • Prototyping and iterating on software
  • Assisting developers on complex work
  • Building AI agents and chatbots
  • Creating RAG-based knowledge apps
  • Deploying LLM apps at enterprise scale
  • Automating recurring business workflows overnight
  • Generating reports, documents and presentations
  • Monitoring uptime, pricing or metrics with auto-actions
  • Running research and content tasks hands-off
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