DEV Community: Atikur Rabbi

Run LLMs Completely Offline on Your Phone: A Practical Guide

Atikur Rabbi — Thu, 04 Dec 2025 05:22:51 +0000

Local LLMs on mobile are now a reality — thanks to powerful apps like Anything LLM, you can run AI models offline directly on your smartphone. No cloud. No data sharing. Fully private.

In this post, you'll learn:

What local mobile LLMs are
Why offline AI is becoming popular
How to install and use Anything LLM on your phone
A short step-by-step setup tutorial

🔗 GitHub Link

Anything LLM Repository: https://github.com/Mintplex-Labs/anything-llm

📱 What is a Local LLM on Mobile?

A Local LLM is an AI model that runs directly on your device — not on a server. This means:

🚫 No internet required
🔒 100% private
⚡ Faster response time
🆓 No API key or cost per request

Mobile hardware is now powerful enough to run small-to-medium LLMs using on-device inference.

🎯 Why Use Offline Mobile AI?

Privacy: Your chats never leave your device.
No API Limits: Use the model as much as you want.
Speed: Local inference avoids network delays.
Portability: Use AI anywhere — even without network.

📥 How to Install Anything LLM Mobile

Anything LLM provides mobile app builds that allow you to run local models offline.

1. Download the Mobile App

Visit the GitHub releases page:
👉 https://github.com/Mintplex-Labs/anything-llm/releases

Look for Android (.apk). iOS support may require TestFlight or sideloading depending on release.

2. Install a Local Model

You can load:

GGUF models
Qwen/Qwen2.5
Llama 3
Mistral
Phi models

Choose a small model (1–4B) for best performance.

3. Load the Model in the App

Open Anything LLM Mobile
Go to Local Model
Import or download a GGUF file
Start chatting offline

🚀 Example: Installing a 3B Model

Download a model from HuggingFace (e.g., Qwen 1.8B GGUF)
Place the model file on your phone
Open Anything LLM → Add Model
Select the downloaded file
Begin chatting locally

🎉 Final Thoughts

Running LLMs offline on your mobile unlocks true AI privacy and freedom. Apps like Anything LLM are making local AI easier than ever.

If you value privacy, control, and unlimited usage — on-device LLMs are the future.

Cursor Free Alternative: Open Source AI Editor using VScode

Atikur Rabbi — Tue, 15 Oct 2024 07:32:46 +0000

Introduction

Cursor is a popular AI-powered IDE built on VS Code. It offers impressive code generation and file management capabilities through prompts, allowing for updates to entire classes or functions with ease. However, it's a closed-source application with a subscription model, raising concerns about cost, enterprise usage limitations, and data security due to its reliance on proprietary servers. This post explores a free, open-source alternative that leverages trusted APIs.

Finding an Open-Source Alternative

Initially, I explored the VS Code extension Claude Dev, which offered similar functionality but only worked reliably with Anthropic's "claude-3-5-sonnet" model. Other models failed to perform file operations.

Cline: A Powerful Alternative

Recently, Claude Dev underwent a significant update, resulting in version 2.0, renamed "Cline". This updated version supports various models and provides functionality comparable to Cursor. Let's explore how to set it up.

Setting up Cline: A Step-by-Step Guide

Step 1: Download and Install Ollama

Go to https://ollama.com/.
Click the "Download" button.
Download the installer appropriate for your operating system (Windows, macOS, or Linux).
Run the installer and follow the on-screen instructions to install Ollama.

Step 2: Download a Language Model

Open the Ollama application.
In the Ollama terminal, use the command ollama pull llama3.2 to download the llama3.2 model. (You can choose other models as well, depending on your preference and needs).
Wait for the download and installation to complete. This may take some time depending on your internet connection and the model size.

Step 3: Install the Cline VS Code Extension

Open VS Code.
Go to the Extensions tab (usually found on the Activity Bar on the side).
Search for "Cline".
Install Cline
Go to Cline setting.
From Api provider Dropdown select Ollama. Select llama3.2 model save the setting by clicking Done button.

Now the setup iss ready and tupe your prompt in input.

Conclusion

Cline provides a compelling open-source alternative to Cursor, offering similar AI-powered coding assistance without the cost and security concerns of a closed-source solution. By leveraging Ollama and a suitable language model, you can enjoy the benefits of AI-assisted coding in a more transparent and secure environment.

Usefull Links Links:

Ollama
Cline

Deploying Spring For Free Using Glitch

Atikur Rabbi — Sun, 05 Sep 2021 16:33:32 +0000

Spring is widely used as JAVA based application framework. It is reliable and lightweight. It is perfect not only for large application but also for our weekend project. Sometimes we need to take our apps live. Unlike node very few free hosting is available for spring. Among them Heroku is most popular.

I like to share one more free hosting option for your spring project. Glitch is providing their free service and we are happy to have a service like this. Many node and frontend developer using their free forever hosting services. Since they support maven I searched for spring project. I failed to found any so I tried to configure one.

Method 1 :

Step 1:

Create your spring project with Spring Initializr or any other tools you prefer

Step 2:

Create a file called glitch.json in your root folder

{
  "start": " java -jar target/*.jar",
  "install": "echo 'compiling' && mvn package",
  "watch": {
    "throttle": 500,
    "install": {
      "include": [
        "^pom\\.xml$",
        "\\.java$"
      ]
    }
  }
}

Step 3:

Upload the project to GitHub and import the project to glitch using git URL. Directly upload the project using glitch file upload is also possible.

Method 2 :

For quick start you can use the remix button / fork button below and customize as you need.

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