qwen
Running a 397B Parameter Model on a Laptop.
Pure C/Metal inference engine that runs Qwen3.5-397B-A17B (a 397 billion parameter Mixture-of-Experts model) on a MacBook Pro with 48GB RAM at 4.4+ tokens/second with production-quality output including tool calling.
The entire 209GB model streams from SSD through a custom Metal compute pipeline. No Python. No frameworks. Just C, Objective-C, and hand-tuned Metal shaders.
Open Source Voice Cloning Desktop App Powered by Qwen3-TTS. Create natural-sounding speech from text with near-perfect voice replication.
The open-source voice synthesis studio. Clone voices. Generate speech. Build voice-powered apps. All running locally on your machine.
Voicebox is a local-first voice cloning studio with DAW-like features for professional voice synthesis. Think of it as a local, free and open-source alternative to ElevenLabs — download models, clone voices, and generate speech entirely on your machine.
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🚀 Cowork with Your AI, Gemini CLI, Claude Code, Codex, Qwen Code, Goose CLI, Auggie, and more.
Free, local, open-source Cowork for Gemini CLI, Claude Code, Codex, Opencode, Qwen Code, Goose Cli, Auggie, and more |
If you have installed command-line tools like Gemini CLI, Claude Code, CodeX, Qwen Code, Goose AI, Augment Code, AionUi can automatically detect them and provide a unified graphical interface
Qwen Code is a coding agent that lives in the digital world.
Qwen Code brings the capabilities of advanced code models to your terminal in an interactive Read-Eval-Print Loop (REPL) environment. Qwen Code consists of a client-side application (packages/cli) that communicates with a local server (packages/core). Qwen Code also contains a variety of tools for tasks such as performing file system operations, running shells, and web fetching, which are managed by packages/core.
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The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.
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