Msty: Local AI Desktop App with Multi-Model Support
Msty is a privacy-first desktop AI application built around one powerful idea: compare responses from multiple models side by side. Connect your local Ollama models, cloud APIs, or any OpenAI-compatible server — then run prompts across all of them simultaneously to find the best model for each task.
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Msty is a standalone desktop app available for macOS, Windows, and Linux. Download from msty.app — no package manager or Docker required.
# macOS
# Download from https://msty.app/download or:
brew install --cask msty
# Windows
# Download installer from https://msty.app/download
# Linux (AppImage)
# Download from https://msty.app/download
chmod +x Msty-*.AppImage
./Msty-*.AppImage
# After installation, connect your local backends:
# 1. Open Msty > Settings > Models > + Add Provider
# 2. Select "Ollama" — URL: http://localhost:11434
# 3. Select "LM Studio" — URL: http://localhost:1234
# 4. For cloud: add OpenAI, Anthropic, Groq API keys
# 5. Models appear in the model selector dropdown
# Prerequisites for local models:
# - Install Ollama: brew install ollama
# - Pull models: ollama pull llama3.2 mistral gemma3 Multi-Model Comparison
Msty's split-panel view is its defining feature. Send one prompt to multiple models and compare outputs in real time — perfect for model selection and quality evaluation:
# How to use multi-model comparison in Msty:
# 1. Click "New Comparison" or use the split-view button
# 2. Select models for each panel, for example:
# Panel 1: llama3.2:7b (local via Ollama)
# Panel 2: mistral:7b (local via Ollama)
# Panel 3: gpt-4o-mini (OpenAI cloud)
# Panel 4: claude-3-5-haiku (Anthropic cloud)
# 3. Type your prompt once in the shared input bar
# 4. All panels respond simultaneously (streaming)
# Great comparison use cases:
# - "Write a regex to validate email addresses"
# → compare accuracy and explanation quality
# - "Summarize this 500-word article in 3 bullet points"
# → compare conciseness and accuracy
# - "Write a unit test for this Python function"
# → compare code quality and coverage
# - "Explain quantum entanglement to a 10-year-old"
# → compare clarity and creativity
# Save comparisons to reference later via the star/bookmark feature Conversation Branching & Organization
Msty lets you fork conversations at any message — useful when you want to explore different approaches without losing the original thread:
Conversation Branching
- • Hover over any message → click "Branch"
- • Creates a new conversation from that point
- • Original conversation remains unchanged
- • Branches share the same conversation history up to the fork point
- • Compare different follow-up directions
Organization Features
- • Topic folders: group chats by project
- • Prompt library: save & reuse system prompts
- • Search: full-text search across all conversations
- • Tags: label conversations for quick filtering
- • Export: save conversations as Markdown or JSON
Msty vs LM Studio vs Jan
| Feature | Msty | LM Studio | Jan |
|---|---|---|---|
| Multi-model comparison | Yes (core feature) | No | No |
| Conversation branching | Yes | No | No |
| Cloud API support | OpenAI, Anthropic, Groq… | Limited | Yes |
| Model management | Via Ollama/LM Studio | Built-in | Built-in |
| Open source | No | No | Yes (MIT) |
| Prompt library | Yes | No | Basic |
| Best for | Model comparison, evaluation | GGUF model management | Privacy + extensibility |
Frequently Asked Questions
What is Msty?▼
Msty is a cross-platform desktop AI application that lets you run and compare multiple AI models simultaneously — both local models (via Ollama, LM Studio, or other local backends) and remote cloud APIs (OpenAI, Anthropic, Groq, Gemini). Its standout feature is the ability to send the same prompt to multiple models and view responses side by side, making it ideal for model evaluation and comparison.
What makes Msty different from other local AI apps?▼
Msty's key differentiators are: (1) Multi-model comparison — run the same prompt on 2, 3, or more models simultaneously and compare responses; (2) Conversation branching — fork a conversation at any point to explore different directions; (3) Topic folders — organize conversations by project or subject; (4) Prompt library — save and reuse prompts; (5) Seamless local + remote model mixing in the same interface.
How does Msty connect to local models?▼
Msty connects to Ollama, LM Studio, Jan, LocalAI, and any other OpenAI-compatible local server. In Settings > Models, add a local provider by specifying the base URL (e.g., http://localhost:11434 for Ollama). Msty then fetches the available models and adds them to your model list alongside cloud models. No configuration files or terminal commands needed.
Does Msty store data locally?▼
Yes. Msty stores all conversation history, settings, and model configurations locally on your device. When using local AI models, no data is sent externally. When using cloud APIs (OpenAI, Anthropic), data goes to those providers under their standard privacy terms. Msty itself does not have its own backend server — it's a pure desktop app.
What is Msty's model comparison feature?▼
In Msty, you can open a 'Split View' and configure multiple model panels. Type a prompt once and it's sent to all active models simultaneously. Responses appear side by side in real time. This is invaluable for: choosing the right model for a task, comparing local vs cloud quality, evaluating model updates, and building intuition about different models' strengths.
Msty vs LM Studio vs Jan?▼
LM Studio focuses on downloading and managing GGUF models with a polished interface. Jan is open-source with an extension system and remote API support. Msty specializes in multi-model comparison and conversation management — features the others lack. If you regularly compare models or want to use both local and cloud models in one app, Msty is the best choice. For pure local model management, LM Studio or Jan may be simpler.
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