--- title: Build a Fully Local Voice Assistant With Whisper and Ollama description: A complete guide to building a fully local, privacy-preserving voice assistant using three open-source components: OpenAI Whisper for speech-to-text, Ollama... canonical: https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Build a Fully Local Voice Assistant With Whisper and Ollama | daily.dev og:description: A complete guide to building a fully local, privacy-preserving voice assistant using three open-source components: OpenAI Whisper for speech-to-text, Ollama... og:url: https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi og:image: https://api.daily.dev/og/posts/LSwpQS4yI.png og:image:alt: Build a Fully Local Voice Assistant With Whisper and Ollama og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Build a Fully Local Voice Assistant With Whisper and Ollama **[Medium](https://daily.dev/sources/medium_js)** · 12 min read · 2 upvotes · 0 comments ## Summary A complete guide to building a fully local, privacy-preserving voice assistant using three open-source components: OpenAI Whisper for speech-to-text, Ollama for running a local language model, and pyttsx3 for text-to-speech. The architecture is a simple four-stage loop: microphone capture, transcription, LLM inference, and speech synthesis — all running on your own machine with no data sent to external servers. The post includes a full working Python script, hardware guidance (from Raspberry Pi to GPU-equipped machines), and tips for improvements like wake-word detection and more natural voices. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do I build a fully local voice assistant using Whisper and Ollama? Chain three local components in a loop: record audio and transcribe it with Whisper, send the text to a local model served by Ollama (such as llama3.2:3b) via its chat API, then speak the reply using a text-to-speech engine like pyttsx3. The whole loop, listen, transcribe, think, speak, runs entirely offline with no data sent to any server. _daily.dev surfaces practical local-AI builds like this for developers wiring together offline voice pipelines._ ### Which Whisper model size should I use for a real-time voice assistant? The base Whisper model, about 140 megabytes, transcribes close to real time on most machines and is accurate enough for everyday speech, making it the sweet spot for a voice assistant. Stepping up to a larger model improves accuracy on tricky audio but adds noticeable delay, so smaller models are preferred when responsiveness matters more than precision. _developers balancing speed and accuracy in speech pipelines can track model trade-offs on daily.dev._ ### How much delay and memory does running a local voice assistant require on different hardware? On a machine with a decent GPU, using a mid-size Whisper model and a three-to-four-billion parameter language model, the full loop responds in about one to two seconds. On a laptop without a strong GPU it still works with smaller models and slightly more delay, and even a Raspberry Pi can run it with tiny models at several seconds of latency. Roughly eight gigabytes of memory is the floor, with sixteen gigabytes making it comfortable. _daily.dev helps developers sizing local AI workloads to their hardware find hands-on guidance like this._ ## Similar posts on daily.dev - [How I Made My Own Offline Voice Assistant](https://daily.dev/posts/how-i-made-my-own-offline-voice-assistant-lvephkfkw) · Medium · 0 upvotes · 0 comments - [Llama.cpp, Speeches, and Open WebUI turned my Raspberry Pi into a voice assistant that actually works](https://daily.dev/posts/llama-cpp-speeches-and-open-webui-turned-my-raspberry-pi-into-a-voice-assistant-that-actually-work-8iedpn70w) · XDA Developers · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#local-ai](https://daily.dev/tags/local-ai), [#speech-recognition](https://daily.dev/tags/speech-recognition), [#ollama](https://daily.dev/tags/ollama), [#whisper](https://daily.dev/tags/whisper) [View this post on daily.dev](https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Build a Fully Local Voice Assistant With Whisper and Ollama","url":"https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi"},"datePublished":"2026-07-23T18:11:21.398Z","dateModified":"2026-09-14T08:41:30.526Z","description":"A complete guide to building a fully local, privacy-preserving voice assistant using three open-source components: OpenAI Whisper for speech-to-text, Ollama...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/64fb9ffc14dcd0a9ad4ae5b9a8f98131?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/64fb9ffc14dcd0a9ad4ae5b9a8f98131?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Medium","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Medium","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium","url":"https://daily.dev/sources/medium_js"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"python,local-ai,speech-recognition,ollama,whisper","timeRequired":"PT12M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Medium","item":"https://daily.dev/sources/medium_js"},{"@type":"ListItem","position":3,"name":"Build a Fully Local Voice Assistant With Whisper and Ollama"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/build-a-fully-local-voice-assistant-with-whisper-and-ollama-lswpqs4yi#faq","mainEntity":[{"@type":"Question","name":"How do I build a fully local voice assistant using Whisper and Ollama?","acceptedAnswer":{"@type":"Answer","text":"Chain three local components in a loop: record audio and transcribe it with Whisper, send the text to a local model served by Ollama (such as llama3.2:3b) via its chat API, then speak the reply using a text-to-speech engine like pyttsx3. 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