🔖 No cloud. No internet. No coding.
🔖 Just you, your laptop, and 100+ powerful AI models running locally.
Imagine building your own chatbot that can answer your questions, summarize documents, analyze images, and even understand tables, all without needing an internet connection.
Sounds futuristic?
Thanks to Model HQ, this is now a reality.
Model HQ developed by LLMWare, is an innovative application that allows you to create and run a chatbot locally on your PC or laptop without an internet connection. Best of all, this can be done with NO CODE in less than 10 minutes, even on older laptops up to 5 years old, provided they have 16GB or more of RAM.
In this guide, we’ll walk you through how to create your own local chatbot using Model HQ ; a revolutionary AI desktop app by LLMWare.ai. Whether you’re a student, developer, or a professional looking for a private and offline AI assistant, this tool puts the power of cutting-edge AI models directly on your laptop.
Let’s break it down.
If you want to know about Model HQ in detail, then read the blog below:
Step 1: Download Model HQ
Model HQ is an AI desktop application that allows you to interact with over 100+ top-performing AI models, including large ones with up to 32 billion parameters — all running locally on your PC.
Unlike cloud-based tools, there’s no internet required, and your data never leaves your machine. That means more privacy, better speed, and zero cost for each query you run.
In this blog, we will be looking into the CHAT feature of Model HQ that helps us to create a chatbot running locally on our machine.
First, get the app.
👉 Download or Buy Model HQ for Windows
Not ready to buy? No problem.
👉 Join the 90-Day Free Developer Trial
Once installed, you’ll have access to an interface that feels like your own AI control panel.
Step 2: Choosing the Right AI Model
Once installation is done, open the ModelHQ application, and then you will be prompted to add a setup method. The setup guide is provided after buying the application.
After this, you will land in the main menu. Now, click on the Chat button.
You’ll be prompted to select an AI model. If you’re unsure which model to choose, you can click on “choose for me,” and the application will select a suitable model based on your needs. Model HQ comes up with 100+ models.
Available Model Options:
Small Model:
~1– 3 billion parameters:- Fastest response time, suitable for basic chat.Medium Model:
~7– 8 billion parameters:- Balanced performance, ideal for chat, data analysis, and standard RAG tasks.Large Model:
~9 – up to 32 billion parameters:- Most powerful chat, RAG, and best for advanced and complex analytical workloads.
By the way, Model HQ will pick a smart default based on your system and use case.
The size of the model you choose can significantly impact both speed and output quality. Smaller models are faster but may provide less detailed responses. Follow this simple rule:
Step 3. Downloading Models
For demonstration purposes, we are selecting the Small Model.
If no models have been downloaded previously (e.g., in the No Setup, Fast Setup, or Full Setup paths), the selected model will begin downloading automatically.
This process typically takes 2–7 minutes, depending on the model you selected and your internet speed.
This is only a one-time internet requirement; once the models are downloaded, you don’t need internet anymore.
Step 4: Start Chatting
Once you’ve selected a model, you can start a chat by typing in your questions. For example, you might ask a simple question like, “What are the top sites to see in Paris?” The model will generate a response based on its training data.
Customizing Your Chat Experience
Model HQ allows you to customize your chat experience further. You can adjust settings such as the maximum output length and the randomness of the responses (known as temperature). By default, the app is set to generate up to 1,000 tokens, which is usually sufficient for smaller models. However, even if you’re using larger models, be cautious about increasing this limit, as it can consume more memory and take longer to generate responses. So, in short, you can adjust generation settings:
Max Tokens: How long should the response be?
Temperature: Should the answer be creative or precise?
Stop/Restart: Hit ❌ to stop a long generation anytime.
Step 5: Integrating Sources for Enhanced Responses
One of the standout features of Model HQ is its ability to integrate sources, such as documents and images, into your chat. To do this, simply click on the “source” button and upload a file, such as a PDF or Word document.
Example: Using a Document as a Source
For instance, if you upload an executive employment agreement, you can ask specific questions about the clauses within the document. The model will reference the uploaded document to provide accurate answers. This feature is invaluable for fact-checking and ensuring that you have the right information at your fingertips.
Chatting with Images
Model HQ also allows you to chat with images. By uploading an image, the application can analyze the content and answer questions based on what it sees. This capability opens up a world of possibilities for multimedia processing, all done locally on your machine without any additional costs.
Step 6: Saving and Downloading Results
After you’ve finished your session, you can save the chat results for future reference. This is particularly useful if you need to compile information for reports or presentations. Simply download the results, and you’ll have everything you need at your fingertips.
Step 7: Exploring Advanced Features
As you become more comfortable with Model HQ, you can explore its advanced features. For example, you can experiment with different models to see how they perform with various types of queries. You can also adjust the generation settings to fine-tune the responses based on your specific needs.
If you’re a visual learner, then watch this YouTube walkthrough:
Future Updates and Community Engagement
Stay engaged with the Model HQ community by following their updates and tutorials on platforms like YouTube. The Model HQ YouTube playlist offers valuable insights and tips to help you maximize your experience with the application.
Join the LLMWare’s Official Discord Server to interact with LLMWare’s great community of users and if you have any questions or feedback.
Why This Matters
Most AI apps require you to upload data to a cloud server. That’s slow, often expensive, and puts your privacy at risk.
With Model HQ, everything runs on your own machine with:
✅ No internet needed
✅ No Coding Required
✅ No API keys or credits
✅ No data leaves your PC
✅ Zero cost per query
It’s your personal AI lab, fully private and offline.
Conclusion: Get Started with Model HQ Today!
Creating a chatbot that runs locally without coding and an internet connection has never been easier. With Model HQ, you have access to a powerful AI tool that can enhance your productivity and streamline your workflow.
Ready to experience the future of AI? Visit the LLMWare website to learn more about Model HQ and its features. Don’t forget to sign up for the 90-day free trial for developers here and explore the application firsthand. When you’re ready to make the leap, you can purchase Model HQ directly here.
Unlock the full potential of AI on your PC or laptop with Model HQ today, and take the first step towards creating your very own local chatbot!
Top comments (20)
Interesting for beginners, but I think calling this “building a chatbot” sets the bar too low. You’re not building — you’re wiring pre-built models through GUI steps. There’s value in accessibility, but let’s not confuse orchestration with engineering. This isn't "AI development", It’s tool usage. A real chatbot comes from training models, building architectures, and understanding the core.
Yes, it is. You can also train the model from your dataset. Try to explore model hq once. It's more likely for enterprise
But you can't use it on PC from 2008 like AMD Phenom™ Triple-Core Processor (2.40 GHz) with 2 GB RAM (total) DDR2 and no GPU. By low level mathematics and everything from scratch, you can train even a Transformer model (same as described in the paper) with deep stack on this PC in minutes.
Specifications are already mentioned, that's why. Everything needs an upgrade, and running AI models locally and privately, without internet, was still an imagination before the launch of Model HQ.
If it provides no comfort to the user, then there's no sense in launching it. 😉
Model HQ makes things easier, sure — but true capability isn’t tied to hardware upgrades. It’s about what you can build when all you have are fundamentals. When you design a model yourself using low-level math and stats — without bloated frameworks — the entire model can be under 150 KB, versus Model HQ’s multi-GB setups that demand 16 GB RAM just to run.
I'm totally getting you, but it's just not limited to a simple chat bot.
You can do RAG, you can create agents, you can do multi-docs RAG, and a lot of features. The RAM requirement is according to the model size and runtime behaviour.
Please read this once: dev.to/llmware/how-to-run-ai-model...
Really appreciate how you broke down the steps, it's wild seeing what local AI can do now with zero coding needed.
Curious, have you noticed any surprising use cases pop up since you’ve started using Model HQ offline?
Thanks for reading.
Yups, there are so many that's why we built Model HQ.
Will try it out for sure! Nice explanation!🙌
Great!
This is amazing @rohan_sharma
Thanks Nishant!
This is extremely impressive, honestly. I've wanted to keep things offline for ages and you made it look so doable
Yuss, try it once!!
What's your thought on this?
I'm planning to try out ModelHQ. I recently downloaded an LLM and was running it through the terminal. ModelHQ seems like a replacement for that, but it’s quite resource-intensive. I was using a 3GB model, and even with that, RAM usage spiked to 100%. It makes me wonder how much RAM would be needed for models over 32GB 🤯. It gets really challenging to use when your project itself is also consuming a lot of memory.
Hi @thevaibhavmaurya , running an LLM is quite memory intensive. However, we are able to run models up to 32 GB on device by optimizing the models for the specific hardware you are using. But to your point, running models on device does consume a lot of memory, period. Our product itself does not consume a lot of memory - it is barely 80 MB for Qualcomm devices and 140 MB for Intel (about the size of a PowerPoint or PDF presentations).
Thanks for the insight! Looking forward to exploring it.
great
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