Comparison·Updated March 2026
fazm.

Fazm vs Simular AI

A voice-first, open-source desktop agent vs an autonomous computer agent from ex-DeepMind researchers. Two approaches to AI on macOS - here's how they compare.

Key difference

Two philosophies. Very different experiences.

Both Fazm and Simular AI can control your desktop. But they take fundamentally different approaches to how you interact with them and how they see your screen.

fazm.

Fazm's approach

Voice-first + accessibility API

  • Voice-first input

    Push-to-talk with one keyboard shortcut. Speak naturally and Fazm acts.

  • Accessibility API

    Reads the macOS accessibility tree for instant, precise element targeting. No screenshots needed.

  • Local screen analysis

    Processes your screen locally before anything leaves your machine.

  • Knowledge graph

    Indexes your files and builds persistent context across sessions.

Simular's approach

Text chat + screenshot grounding

  • Text-only input

    Type instructions into a chat interface. No voice control available.

  • Screenshot-based vision

    Captures screenshots and uses vision models to identify UI elements. Agent S2 dropped accessibility trees entirely.

  • Cloud LLM processing

    Screenshots sent to cloud-hosted models (GPT-4, Claude, etc.) for analysis and decision-making.

  • Neuro-symbolic replay

    Records successful workflows and converts them into deterministic, repeatable code.

Feature-by-feature comparison

How Fazm and Simular AI stack up across every dimension.

Fazm
Simular AI
Scope
Entire macOS desktop - any app
Desktop apps via screenshot analysis
Primary input
Voice + text (push-to-talk)
Text chat only
Context awareness
Any screen + local files + knowledge graph
Current screen via screenshots
Desktop control
Native macOS accessibility API
Screenshot-based visual grounding (Agent S2+)
Voice control
Native push-to-talk
No voice input
File access
Indexes files, builds knowledge graph
Can interact with files via GUI
Privacy
Screen analysis runs locally
Screenshots sent to cloud LLMs
Open source
Yes - fully open source
Partially - Agent S framework only
Pricing
Free & open source
Paid plans (Plus, Pro, Enterprise)
Task replay
Intelligent automation
Record and replay workflows
Platform
macOS (Windows planned)
macOS, Windows
App integration
Google Workspace, VS Code, any app
Any visible GUI application
Input

Talk to your Mac. Don't type at it.

Fazm is built around voice - push-to-talk with one keyboard shortcut. Simular AI requires you to type instructions into a chat interface, adding friction to every interaction.

F
Fazm
  • Push-to-talk voice input
  • Natural language commands
  • One keyboard shortcut to activate
  • Instant transcription
Simular
  • Text-only chat input
  • No voice control
  • Type every instruction
  • No hands-free option
Desktop control

Accessibility API vs screenshots

Fazm uses the macOS accessibility API for precise, instant interaction with UI elements. Simular AI relies on screenshot-based visual grounding - taking screenshots and using vision models to identify where to click. The accessibility API is faster, more reliable, and doesn't require sending images to cloud servers.

F
Fazm
  • macOS accessibility API
  • Sub-second element targeting
  • Reads full UI structure
  • No screenshots needed
Simular
  • Screenshot-based grounding
  • Vision model identifies UI elements
  • Depends on visual recognition
  • Requires image processing
Privacy

Your screen stays on your Mac

Fazm processes screen analysis locally before anything leaves your machine. Simular AI captures screenshots of your desktop and sends them to cloud-hosted LLMs for visual grounding and decision-making. If your screen shows sensitive data, that data goes to the cloud.

F
Fazm
  • Screen analysis runs locally
  • Data stays on your Mac
  • No screenshots sent to servers
  • Privacy by architecture
Simular
  • Screenshots sent to cloud LLMs
  • Requires external model APIs
  • Screen data leaves your machine
  • Cloud-dependent processing
Open source

Fully open vs partially open

Fazm's entire codebase is open source on GitHub - the agent, the UI, everything. Simular open-sources their Agent S research framework, but the actual Simular Desktop product is proprietary and requires a paid subscription for full features.

F
Fazm
  • Entire project is open source
  • Inspect and modify any code
  • Community contributions welcome
  • No vendor lock-in
Simular
  • Agent S framework is open source
  • Desktop product is proprietary
  • Paid subscription required
  • Limited community access to product
Context

Knows your files. Understands your workflow.

Fazm indexes your local files and builds a knowledge graph so it understands what you're working on. Simular sees what's on screen and can interact with visible UI elements, but doesn't build a persistent understanding of your workspace.

F
Fazm
  • Indexes local files
  • Builds knowledge graph
  • Persistent context across sessions
  • Understands your projects
Simular
  • Sees current screen only
  • No local file indexing
  • Session-based context
  • Task-focused, not workspace-aware

About each product

Simular AI

by Simular (ex-DeepMind)

An autonomous computer agent built by former Google DeepMind researchers. Raised $21.5M Series A led by Felicis, with NVentures (Nvidia) participating. Uses a “neuro-symbolic” approach where the LLM writes code that becomes deterministic and repeatable. Their open-source Agent S framework scores 72.6% on OSWorld with Behavior Best-of-N. The commercial Simular Desktop product offers task recording and replay, screenshot-based visual grounding, and supports both macOS (15+ with Apple Silicon) and Windows. Pricing includes Plus, Pro, and Enterprise tiers.

fazm.

Fazm

Open source

An AI computer agent for macOS that goes beyond the browser. Controls your mouse, keyboard, browser DOM, and native apps - all triggered by voice. Indexes local files, builds a knowledge graph, and integrates with Google Workspace. Screen analysis runs locally for privacy. Uses the macOS accessibility API for precise, sub-second element targeting rather than screenshot-based vision. The entire project is open source. Free to use with no subscription required.

Technical deep-dive

Accessibility API vs screenshot grounding

The way an agent “sees” your screen determines its speed, accuracy, and privacy. Fazm and Simular take opposite approaches.

fazm.

Fazm

macOS accessibility API

  • Reads the full accessibility tree - knows every element, label, and state
  • Sub-second element targeting without vision model inference
  • Works reliably even when UI looks different across themes
  • No screenshots captured or sent anywhere
  • Deterministic element identification by role and label
  • Processes screen structure locally on your Mac

Simular AI

Screenshot-based visual grounding

  • Agent S2 operates solely on raw screenshots as input
  • Uses specialized vision models to identify UI elements
  • Earlier Agent S used accessibility trees, but S2 dropped them
  • Screenshots sent to cloud LLMs for analysis
  • Visual recognition can fail on unusual UI layouts
  • Requires cloud round-trip for each screen observation

Simular's Agent S framework achieves impressive benchmark scores, but its screenshot-based approach means your screen data goes to cloud servers for every action. Fazm's accessibility API approach is faster, more private, and doesn't depend on a vision model correctly interpreting pixels.

When to use which

Choose Fazm if you...

  • Want voice-first control over your Mac
  • Care about privacy - screen data stays local
  • Prefer fully open-source software you can inspect
  • Need a free tool with no subscription required
  • Want fast, accessibility-API-based desktop control
  • Need file indexing and persistent workspace context

Choose Simular if you...

  • Want to record and replay workflow automations
  • Need Windows support today
  • Want the neuro-symbolic approach for deterministic tasks
  • Are okay with paid subscription plans
  • Prefer text-based chat interaction over voice

Ready to try the voice-first approach?

Download Fazm for macOS and see what a voice-first, open-source desktop agent can do. Free forever.