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LocalMode
Run AI in your browser - no servers, no API keys
LocalMode is an open-source (MIT) toolkit for running AI entirely in the browser: LLM chat over 76 models, RAG, speech, and vision. No servers, no API keys, and data never leaves the device. WebGPU with a WebAssembly fallback; works offline.
I built LocalMode because "AI in your app" almost always means shipping your users' data to someone else's servers, wiring up API keys, and paying per token. I wanted the opposite: AI that runs entirely in the browser, where the data never leaves the device.
LocalMode is an open-source (MIT) toolkit for exactly that:
• LLM chat over 76 models across 5 runtimes (Transformers.js, WebLLM, wllama, LiteRT, MediaPipe) + Chrome Built-in AI • RAG and vector search - embeddings, a vector DB, and semantic search • Speech - Whisper speech-to-text and Kokoro text-to-speech (29 voices) • Vision - image classification, object detection, and CLIP image search • A zero-dependency core, 64 React hooks, and a shadcn UI registry of 107 components + 36 installable blocks • Runs on WebGPU with a WebAssembly fallback, and works offline after the first model download
No servers. No API keys. No telemetry. It's MIT-licensed and the whole thing is copy-owned - install a block with the shadcn CLI and you own the .tsx.
I'd love feedback on which capability you'd reach for first, and what's missing. Happy to answer anything in the comments today 🙏
About LocalMode on Product Hunt
“Run AI in your browser - no servers, no API keys”
LocalMode was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #48 on the daily leaderboard. LocalMode is an open-source (MIT) toolkit for running AI entirely in the browser: LLM chat over 76 models, RAG, speech, and vision. No servers, no API keys, and data never leaves the device. WebGPU with a WebAssembly fallback; works offline.
On the analytics side, LocalMode competes within Open Source, Developer Tools, Artificial Intelligence, GitHub and Vercel Day — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how LocalMode performed against the three products that launched closest to it on the same day.
Who hunted LocalMode?
LocalMode was hunted by LocalMode AI. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of LocalMode including community comment highlights and product details, visit the product overview.
LocalMode AI
Hey Product Hunt 👋
I built LocalMode because "AI in your app" almost always means shipping your users' data to someone else's servers, wiring up API keys, and paying per token.
I wanted the opposite: AI that runs entirely in the browser, where the data never leaves the device.
LocalMode is an open-source (MIT) toolkit for exactly that:
• LLM chat over 76 models across 5 runtimes (Transformers.js, WebLLM, wllama, LiteRT, MediaPipe) + Chrome Built-in AI
• RAG and vector search - embeddings, a vector DB, and semantic search
• Speech - Whisper speech-to-text and Kokoro text-to-speech (29 voices)
• Vision - image classification, object detection, and CLIP image search
• A zero-dependency core, 64 React hooks, and a shadcn UI registry of 107 components + 36 installable blocks
• Runs on WebGPU with a WebAssembly fallback, and works offline after the first model download
No servers. No API keys. No telemetry. It's MIT-licensed and the whole thing is
copy-owned - install a block with the shadcn CLI and you own the .tsx.
Try the live blocks (chat, RAG, vision, voice - all running in your tab): 👉 https://localmode.ai/blocks
UI Components: https://localmode.ai
Docs: https://localmode.dev
GitHub: https://github.com/LocalMode-AI/...
I'd love feedback on which capability you'd reach for first, and what's missing.
Happy to answer anything in the comments today 🙏