ChatGPT
AI conversational assistant for answering questions, writing, and coding help
NextChat
Lightweight AI assistant supporting Claude, GPT-4, and Gemini
Cross-platform AI chat interface with multi-model support, privacy-first local storage, and one-click deployment. Includes prompt templates, plugin system, and desktop apps.
Overview
Overview
NextChat is a lightweight, fast AI assistant that provides a unified interface for leading language models including Claude, DeepSeek, GPT-4, and Gemini Pro. Designed for developers and teams seeking a privacy-focused chat experience, it stores all data locally in the browser and supports self-hosted LLM deployments.
Capabilities
The platform offers a compact client (~5MB) available for Linux, Windows, and macOS, with PWA support for web deployment. Users can create and share custom prompt templates, leverage an extensible plugin system for network search and calculations, and preview generated content through the Artifacts feature. Markdown rendering includes LaTeX, Mermaid diagrams, and syntax highlighting. The interface supports 14+ languages and features responsive design with dark mode.
Deployment
Deploy to Vercel with one click or self-host with compatible LLM backends like RWKV-Runner and LocalAI. The application compresses chat history automatically to optimize token usage during long conversations. Enterprise editions offer brand customization, centralized resource management, permission controls, and private cloud deployment options. Access control is configurable via environment variables for team environments.
Highlights
Multi-model support: Claude, GPT-4, Gemini Pro, DeepSeek, and self-hosted LLMs
Privacy-first architecture with local browser storage and optional self-hosting
Cross-platform desktop apps (~5MB) and one-click Vercel deployment
Extensible plugin system, prompt templates, and Artifacts preview window
Pros
- Extremely lightweight client with fast loading times (~100kb first screen)
- Works with self-deployed LLMs and multiple commercial AI providers
- Comprehensive internationalization support across 14+ languages
- Active development with plugin system, realtime chat, and MCP support
Considerations
- Limited access control relies on environment variable configuration
- Enterprise features require separate commercial licensing
- Automatic updates on Vercel require manual fork setup
- iOS source code not yet publicly available
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Fit guide
Great for
- Developers wanting a unified interface for multiple AI models
- Privacy-conscious users preferring local data storage
- Teams needing quick deployment with minimal infrastructure overhead
- Organizations running self-hosted LLM infrastructure
Not ideal when
- Users requiring advanced enterprise access controls out-of-the-box
- Teams needing built-in compliance auditing without enterprise edition
- Organizations wanting vendor-managed hosting with SLA guarantees
- Non-technical users unfamiliar with API key management
How teams use it
Multi-Model Development Testing
Developers compare Claude, GPT-4, and Gemini responses side-by-side using custom prompt templates to identify optimal models for specific tasks.
Privacy-Compliant Internal Tool
Organizations deploy NextChat with self-hosted LLMs to maintain data sovereignty while providing employees AI assistance for documentation and code review.
Rapid Prototyping with Artifacts
Designers generate and preview HTML/CSS prototypes in the Artifacts window, iterating quickly without leaving the chat interface.
Multilingual Customer Support
Support teams use the 14-language interface with network search plugins to assist international customers across time zones with consistent AI-powered responses.
Tech snapshot
TypeScript92%
SCSS7%
JavaScript1%
Rust1%
Shell1%
Dockerfile1%
Frequently asked questions
What AI models does NextChat support?
NextChat supports Claude, DeepSeek, GPT-4, Gemini Pro, and self-hosted models through RWKV-Runner or LocalAI including llama, gpt4all, vicuna, and falcon.
How is data stored and is it private?
All chat data is stored locally in your browser by default. For self-hosted deployments, data remains on your infrastructure. Enterprise editions offer additional security auditing and private cloud options.
Can I use NextChat without coding knowledge?
Yes. After obtaining an API key from your chosen provider, click the one-click deploy button for Vercel or download the desktop app. Configuration is done through a settings interface.
What are prompt templates and how do they work?
Prompt templates let you create reusable conversation starters with pre-defined context. Save custom prompts, share them with others, or use community templates from awesome-chatgpt-prompts collections.
Does NextChat work offline or with local models?
Yes. NextChat is fully compatible with self-deployed LLMs. Point it to your LocalAI or RWKV-Runner instance to run models entirely on your infrastructure without internet-dependent API calls.
Project at a glance
Active- Stars
- 87,106
- Watchers
- 87,106
- Forks
- 60,533
LicenseMIT
Repo age2 years old
Last commit2 months ago
Self-hostingSupported
Primary languageTypeScript
Last synced 23 hours ago