Alternatives
Products that do what Run LLMs on the Browser does
Deep Chat has just received a huge update! You can now host entire LLMs on the browser. No servers, no connections, run it all in the comfort of your browser. Supported models include popular LLaMA and Mistral LLMs. Check out the Open Source project to add it to your website: https://github.com/OvidijusParsiunas/deep-chat Try it out live in the Deep Chat playground: https://deepchat.dev/playground
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LLM from URL —— A free AI chat completion service directly from URL Usage: In the address bar of any web browser, type your question after https://818233.xyz/ and hit Enter to get the instant answer. You know the best part of this? Whitespace in the url is supported in most web browsers! You can also use curl or Wget to retrieve the appended url by replacing any whitespace with a '+' character. If you need to have an actual '+' character in your question, just use '++'. Example: The url "https://818233.xyz/hi there" in any web browser will return the same answer…
2025 · 818233.xyz
- 13LT
Introducing Lailaims: An open source client-side web app that lets you test multiple LLM providers (GPT-4, Claude, Gemini, Mistral, DeepSeek) side-by-side in one interface. Your data stays private - everything runs locally in your browser! Video example: https://vimeo.com/1084976999/8687b63f85
2025 · lailaims.pages.dev
- 14MA
Hello everyone! I have a hobby project that has become fairly full featured that I figured I would share. The idea of MinimalChat has been to create a project that is a lightweight and dead simple application that can be deployed locally in a few seconds (with docker). While of course also having most of the nice to have features and looking pretty nice. A nice bonus is it a Progressive Web Application so it can be installed like a normal application to your mobile device. It has a full mobile UI. For those using Chrome and Edge you can also locally download, load and host entirely via your…
2024 · github.com
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private, tech, llm, ai, web, webgpu, offline, local, webasm
Aug 2026 · chatbotjames.onrender.com
- 16LC
Hey, folks here is a peek into Jujutsu. We at Poozle are working with hundreds of APIs and it has been always frustrating to 1. Search the API in the documentation or ask ChatGPT 2. Then copy it to the postman and understand/test the API 3. Generate code to integrate into the codebase We thought how about having all of this at one place. We currently fine-tuned LLM on public REST APIs to reduce hallucination and then combined it with ChatGPT and Postman. I look forward to feedback, feature requests and discussions!
2023 · loom.com
- 17IB
hey hn, I built an open-source Perplexity clone that can run local LLMs and cloud LLMs. It's fully self-hostable through Docker and uses ollama to support local LLMs. The demo video in the repository shows me running it locally with llama3 on my M1 Macbook Pro. I'm open to any suggestions or feedback, thanks!
2024 · github.com
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I kept running into this annoying problem: I’d remember a really useful answer, but not where it was. ChatGPT? Claude? Gemini? No idea. So I’d end up digging through all of them or just rewriting the prompt. Built this to fix that. It’s a Chrome extension that indexes chats locally and lets you search across them all in one place. Once it’s indexed, search is basically instant. Still early. UIs change and break things sometimes, so it’s a bit fragile in places. Curious if other people have the same issue or if it’s just me jumping between tools too much.
Apr 2026 · chromewebstore.google.com
- 19OD
I’d like to use LLMs for remembering all kinds of things: fitness, to-do lists, contacts, bug reports, research links, whatever. But there is no way to do that now. For example, if I find a great coding tutorial in chat, or tell it how much I ran yesterday, it forgets that when I close the chat. Even if I keep the chat history, I still need to scour through lots of messages to find the data I want. Ideally, Claude would remember all this, and I’d be able to find it later with ease. This is what my team built. It is a collaborative database you add to any LLM that supports MCP. (Claude Code,…
2025 · dry.ai
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Hi HN! I wanted to share my freshly finished open-source project. It is similar to ChatGPT Code Interpreter, but the interpreter runs locally and it can use open-source models like Llama 2. It allows you to work with sensitive data without uploading it to the cloud. Either you use a local LLM (like Llama 2), or an API (like GPT-4). For the latter case, there is an approval mechanism in the UI, which separates your local data from the remote services. I would be very interested in your valuable feedback!
2023 · github.com
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2023 · github.com
- 22LS
LLMStack is a low-code platform that can be used to build LLM apps, chatbots and integrate AI experiences into existing products/workflows. It comes with everything out of the box that one needs to build LLM apps locally. It can also be used in a multi-tenant setting, making it available for everyone to use in an enterprise. Some highlights of the platform: - Chain multiple LLM models allowing for complex pipelines - Includes a vector database and necessary connectors to help enrich LLM responses with private data - App templates tailored to specific use cases to quickly build LLM apps…
2023 · github.com
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Hi there, looking for feedback on my new project "Featherless.AI" The idea is to allow users to run all the models on hugging face instantly. Via the OpenAI API compatible endpoint. Why? Because its a real chore to download models and spin up GPUs, especially if you want to test multiple models. Not to mention GPUs cost multiple dollars an hour to rent. And if we want more people to use open source AI, we got to make it easier for them to try and play with all of them. So what if instead of spinning up dedicated GPUs per model (which is what every provider is doing) We can startup a LLM…
2024 · featherless.ai
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I've built an airgapped Retrieval-Augmented Generation (RAG) system for question-answering on documents, running entirely offline with local inference. Using Llama 3, Mistral, and Gemini, this setup allows secure, private NLP on your own machine. Perfect for researchers, data scientists, and developers who need to process sensitive data without cloud dependencies. Built with Llama C++, LangChain, and Streamlit, it supports quantized models and provides a sleek UI for document processing. Check it out, contribute, or suggest new features!
2024 · github.com
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