Cherry Studio: A Desktop Client for Multiple LLM Providers and 300+ Assistants
Cherry Studio is a multi-provider LLM desktop client for Windows, macOS and Linux combining smart chat, autonomous agents and 300+ built-in assistants.
At a glance
- What is it?
- Cherry Studio is a cross-platform desktop client that unifies access to cloud, web, and local LLMs, with a library of pre-configured assistants. Its AGPL-3.0 license and Electron-style packaging shape who should adopt it.
- Who is it for?
- Adopt Cherry Studio if you want a single desktop interface for multiple LLM providers, especially if you rely on pre-configured assistants and need local model support via Ollama or LM Studio. Avoid it if you require a permissive license for redistribution or if you prefer a self-hosted, server-based solution.
- Can I use it commercially?
- Yes, with strict conditions. AGPL-3.0 is a network copyleft licence: if people use a modified version over a network, for example as a hosted service, you must offer them its source code under the same licence.
- Is it still maintained?
- Yes. The repository last received commits 1 day ago.
- What is it written in?
- Mainly TypeScript, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 14, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
What Cherry Studio Actually Solves
Cherry Studio targets a specific pain: the proliferation of AI chat interfaces. A user who wants to compare responses from OpenAI, Gemini, and Anthropic must normally keep multiple browser tabs or desktop apps open. Cherry Studio collapses that into one client. The README lists support for major cloud services, AI web services like Claude and Perplexity, and local models via Ollama and LM Studio. The intended user is someone who works across providers daily and wants a consistent interface for chat, documents, and assistants. It is not a server or a library. It is a desktop application, available on Windows, Mac, and Linux, and the README stresses that it is ready to use with no environment setup required. That positioning suggests a non-developer audience, but the MCP support and WebDAV integration hint at power users too.
How the Application Is Structured
The repository is written in TypeScript, which points to an Electron-based desktop app, though the README does not explicitly confirm the framework. The architecture is client-side: all provider API keys and conversation data live on the user's machine. The client talks directly to each provider's API, so there is no central proxy. The multi-model simultaneous conversation feature means a single topic can be sent to several models at once, and the interface shows all responses side by side. The 300+ pre-configured assistants are likely prompt templates bundled with the app, and users can create custom assistants. The MCP server support allows external tools to be connected, which extends the client beyond simple chat. The README mentions MCP Marketplace as a roadmap item, so the current MCP support is probably basic server configuration rather than a full ecosystem.
Getting Started and Configuration
Because Cherry Studio is a desktop client, installation is straightforward: download the release for your platform from the GitHub releases page, which lists versions like v2.0.10. No build step is needed for end users. After launching, the user configures each provider by entering an API key. The README does not give the exact settings menu path, but it says the client supports OpenAI, Gemini, Anthropic, and web services like Poe. For local models, the user must have Ollama or LM Studio running, and then point Cherry Studio to the local endpoint. The README does not specify the default port, so a user may need to check Ollama's documentation. The WebDAV feature requires a server URL and credentials, which are entered in the settings. The client also supports themes, which can be installed from external repositories like the Aero theme or PaperMaterial. Those themes are separate GitHub projects, so the user must download and apply them manually.
Document Handling and Knowledge Features
Cherry Studio goes beyond chat by supporting document upload and processing. The README lists text, images, Office files, and PDF as supported formats. This suggests the client can extract text from these files and send it to a model for analysis. The Mermaid chart visualization and code syntax highlighting are rendering features that make model output more readable. The WebDAV integration serves two purposes: file management and backup. A user can store conversation data or documents on a WebDAV server, which is useful for syncing across machines. The roadmap includes notes, collections, and OCR, but those are not yet implemented. The current document support is a differentiator compared to a plain chat client, but the README does not describe how the document processing works under the hood. It may simply send raw text or use a local parser. Without more detail, a user should test with a complex PDF to see if formatting survives.
Limitations and Gaps in the Current Version
The roadmap is the clearest source of limitations. Cherry Studio has no plugin system yet, which limits extensibility beyond the built-in MCP support. Mobile platforms are not covered: Android and iOS are both in phase 1 of the roadmap. HarmonyOS is also pending. Multi-window support and window pinning are not available. The README mentions a selection assistant and deep research as core features still in development, so the current version lacks advanced research workflows. The MCP Marketplace is a roadmap item, meaning the current MCP configuration is manual and may not be user-friendly. The document preprocessing feature is also future work, so the current document handling may be basic. These gaps matter for an engineer who wants to deploy Cherry Studio in a team: there is no centralized management, no server component, and no way to push configurations to multiple users. Each user must configure their own API keys and assistants.
Licensing and Commercial Implications
Cherry Studio is licensed under AGPL-3.0. This is a strong copyleft license. If you distribute a modified version of the client, you must release the source code under the same license. The README includes a commercial link, which suggests the project offers a commercial license for companies that do not want to comply with AGPL. This is a common dual-licensing model for open-source desktop apps. For an individual user, the AGPL has no practical impact; you can download and use the client freely. For a company that wants to embed Cherry Studio into a proprietary product or redistribute it, the AGPL is a significant constraint. The README also shows a sponsor link, indicating the project relies on community funding. The maintenance cadence is active: v2.0.9 and v2.0.10 were released within a week of each other in August 2026, and the last push was the same day as v2.0.10. That suggests a fast release cycle, which is good for bug fixes but means upgrades may come frequently.
Alternatives and How They Differ
The main alternative to Cherry Studio is a web-based multi-provider gateway like OpenRouter or a self-hosted solution such as LibreChat. OpenRouter is a proxy that gives you a single API endpoint for many models. The difference is architectural: Cherry Studio is a fat client that talks to each provider directly, while OpenRouter sits in the middle and centralizes billing and API keys. If you want to use Cherry Studio with OpenRouter, you can add OpenRouter as a provider, since it exposes an OpenAI-compatible API. LibreChat is a self-hosted web application that also supports multiple providers and has a plugin system. The key difference is that LibreChat runs on a server and has a web UI, while Cherry Studio is a local desktop app. For a user who wants to access their chats from any device, LibreChat is better. For a user who wants a native desktop experience with offline document handling, Cherry Studio is better. Another alternative is to use each provider's official client, but that means losing the unified interface.
Maintenance and Upgrade Considerations
The release history shows a steady stream of updates, with v2.0.8, v2.0.9, and v2.0.10 all appearing in August 2026. That is a healthy sign for bug fixes and feature additions. However, the README does not describe an upgrade path. Users likely download the new installer from the releases page and replace the old version. There is no mention of automatic updates. For a power user, this means manually checking for new releases. The project board is the place to track progress, and the README invites users to join GitHub Discussions to influence the roadmap. The development contribution guide is linked, so a developer can build from source. The README does not list system requirements, so a user should check the release notes for minimum OS versions. The AGPL license also means that if you modify the client, you must track and publish your changes if you distribute them. That is a maintenance cost for any organization that forks the project.
Editorial conclusion
Adopt Cherry Studio if you want a single desktop interface for multiple LLM providers, especially if you rely on pre-configured assistants and need local model support via Ollama or LM Studio. Avoid it if you require a permissive license for redistribution or if you prefer a self-hosted, server-based solution. Before adopting, verify that the AGPL-3.0 terms fit your use case, and check the project board for roadmap items like plugins and mobile support, which are not yet available.
Community notes