Excited to see what the community has built with SGLang-Omni!
SGLang-Omni enables community-built projects
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SGLang (@sgl_project) posts that it is excited to see what the community has built with SGLang-Omni. The quoted post says Voxt, an open-source Mac voice input tool, now runs SGLang Omni in its inference stack for local speech recognition, with the MLX branch handling speech recognition.
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It’s a pleasure to introduce and demo Voxt, an open-source voice input tool for Mac. Voxt has been actively developed for over six months, shaped by real-world use and feedback from more than a thousand users. With this update, we’re bringing SGLang Omni into Voxt’s inference stack to further improve local inference performance. We’ll also continue refining the overall user experience. There are already plenty of voice input tools available. Typeless, Doubao Input Method, Zhipu Input Method, and WeChat Input Method all offer these capabilities. Voxt’s strength is its open, controllable software stack: we can continuously optimize everything from the application to inference, improving both performance and stability. With a fully local configuration, speech recognition and text refinement run entirely on your own computer, so your audio and transcriptions don’t need to be uploaded to a remote inference service. Today, we’ll focus on how Voxt handles technical terminology, particularly model names, framework names, and English acronyms used in AI engineering. Basic ASR alone can easily misrecognize these terms. Voxt combines hotword recognition, LLM-based text refinement guided by a personal system prompt, and inference performance optimizations. Together, these make voice input efficient, improve its handling of technical vocabulary, and adapt it to your own style of expression. This demo runs on my M5 Pro Mac. Speech recognition uses SGLang Omni’s MLX branch, while text refinement uses Qwen3.8 27B running locally through Ollama Serve. Both steps run on this machine. Voxt also provides interfaces for both ASR and LLMs. You can choose remote speech recognition services and remote language models to suit your needs—you’re not limited to the local setup shown in this demo. Xuesong and I have been using Voxt for over six months, and we’ve gone from everyday users to contributors. Integrating SGLang Omni marks another milestone in our collaboration. Thank you to Guan Wei and everyone involved. We invite you to download Voxt, give it a try, and help us make it even better. Acknowledgments: Guan Wei · Ye Xuesong · Liu Chonghan · Zhou Yuhan · Deng Jiaxin Project: https://github.com/sgl-project/sglang-omni/tree/main/Voxt Download: https://github.com/sgl-project/sglang-omni/releases#release-voxt-v1.16.0
Source: SGLang · x.comPublished