Deploying Qwen3-4B on Hyperstack: A Step-by-Step Guide

What is Qwen3-4B?

Qwen3-4B is part of the latest generation of Qwen large language models, designed to push the boundaries of reasoning, dialogue, and multilingual support. It is a causal language model with 4 billion parameters, making it compact yet powerful for a wide range of tasks. Built on both pre-training and post-training, Qwen3-4B delivers strong performance in logical reasoning, mathematics, coding, and natural conversation, while also excelling in instruction following, role-playing and multi-turn dialogues.

Features of Qwen3-4B

Here are the key features of Qwen3-4B:

• Dual Reasoning Modes: Switches between deep thinking mode for maths, coding, and reasoning, and fast mode for casual conversations, ensuring both speed and accuracy.
• Stronger Problem-Solving: Delivers more accurate results in logic, mathematics, and code generation compared to earlier Qwen models, making it reliable for technical tasks.
• Human-Like Conversations: Excels at instruction following, creative writing, role-play, and multi-turn dialogue, creating smooth and engaging interactions.
• Advanced Agent Capabilities: Integrates with external tools across different modes, allowing it to handle complex workflows and act as a smart assistant.
• Multilingual Support: Covers 100+ languages and dialects with robust translation and instruction-following, making it useful for global communication.

How to Deploy Qwen3-4B

Now, let's walk through the step-by-step process of deploying Qwen3-4B on Hyperstack.

Step 1: Accessing Hyperstack

1. Go to the Hyperstack website and log in to your account.
2. If you're new to Hyperstack, you'll need to create an account and set up your billing information. Check our documentation to get started with Hyperstack.
3. Once logged in, you'll be greeted by the Hyperstack dashboard, which provides an overview of your resources and deployments.

Step 2: Deploying a New Virtual Machine

Initiate Deployment

1. Look for the "Deploy New Virtual Machine" button on the dashboard.
2. Click it to start the deployment process.

Select Hardware Configuration

1. In the hardware options, choose the "1xH100 PCIe" flavour.

Choose the Operating System

1. Select the "Ubuntu Server 24.04 LTS R570 CUDA 12.8 with Docker".

Select a keypair

1. Select one of the key pairs in your account. Don't have a keypair yet? See our Getting Started tutorial for creating one.

Network Configuration

1. Ensure you assign a Public IP to your Virtual machine.
2. This allows you to access your VM from the internet, which is crucial for remote management and API access.

Enable SSH Access

1. Make sure to enable an SSH connection.
2. You'll need this to securely connect and manage your VM.

Review and Deploy

1. Double-check all your settings.
2. Click the "Deploy" button to launch your virtual machine.

Step 3: Accessing Your VM

Once the initialisation is complete, you can access your VM:

Locate SSH Details

1. In the Hyperstack dashboard, find your VM's details.
2. Look for the public IP address, which you will need to connect to your VM with SSH.

Connect via SSH

1. Open a terminal on your local machine.
2. Use the command ssh -i [path_to_ssh_key] [os_username]@[vm_ip_address] (e.g: ssh -i /users/username/downloads/keypair_hyperstack ubuntu@0.0.0.0.0)
3. Replace username and ip_address with the details provided by Hyperstack.

Step 4: Setting up Qwen3-4B with Open WebUI

To access and experiment with Meta's latest model, SSH into your machine after completing the setup. If you are having trouble connecting with SSH, watch our recent platform tour video (at 4:08) for a demo. Once connected, use this API call on your machine to start using the Qwen3-4B:

# 1) Create a docker network
docker network create ollama-net

# 2) Start ollama
sudo docker run -d --gpus=all --network ollama-net -p 11434:11434 -v /home/ubuntu/ollama:/root/.ollama --name ollama --restart always ollama/ollama:latest

# 3) Pull the model
sudo docker exec -it ollama ollama pull qwen3:4b

# 4) Start Open WebUI (points to ollama's API)
sudo docker run -d --network ollama-net -p 3000:8080 -v open-webui:/app/backend/data --name open-webui --restart always -e OLLAMA_BASE_URL=http://ollama:11434 ghcr.io/open-webui/open-webui:main

If the API is not working after ~10 minutes, please refer to our 'Troubleshooting Qwen3-4B" section below.

Interacting with Qwen3-4B

1. Open your VM's firewall settings.

2. Allow port 3000 for your IP address (or leave it open to all IPs, though this is less secure and not recommended). For instructions, see here.

3. Visit http://[public-ip]:3000 in your browser. For example: http://198.145.126.7:3000

4. Set up an admin account for OpenWebUI and save your username and password for future logins. See the attached screenshot.

And voila, you can start talking to your self-hosted Qwen3-4B! See an example below.

Troubleshooting Qwen3-4B

Step 5: Hibernating Your VM

When you're finished with your current workload, you can hibernate your VM to avoid incurring unnecessary costs:

1. In the Hyperstack dashboard, locate your Virtual machine.
2. Look for a "Hibernate" option.
3. Click to hibernate the VM, which will stop billing for compute resources while preserving your setup.

To continue your work without repeating the setup process:

1. Return to the Hyperstack dashboard and find your hibernated VM.
2. Select the "Resume" or "Start" option.
3. Wait a few moments for the VM to become active.
4. Reconnect via SSH using the same credentials as before.

Why Deploy on Hyperstack?

Hyperstack is a cloud platform designed to accelerate AI and machine learning workloads. Here's why it's an excellent choice for deploying Qwen3-4B:

• Availability: Hyperstack provides access to the latest and most powerful GPUs such as the NVIDIA A100 and the NVIDIA H100 SXM on-demand, specifically designed to handle large language models. 
• Ease of Deployment: With pre-configured environments and one-click deployments, setting up complex AI models becomes significantly simpler on our platform. 
• Scalability: You can easily scale your resources up or down based on your computational needs.
• Cost-Effectiveness: You pay only for the resources you use with our cost-effective cloud GPU pricing. 
• Integration Capabilities: Hyperstack provides easy integration with popular AI frameworks and tools.

New to Hyperstack? Sign up on Hyperstack Today to Get Started.

FAQs

What is Qwen3-4B?

Qwen3-4B is a 4-billion parameter causal language model from the Qwen3 series, designed for reasoning, coding, creative writing, multilingual support, and tool integration.

How is Qwen3-4B different from earlier Qwen models?

It introduces dual reasoning modes, offering both deep logical thinking and fast conversational responses, while also showing stronger performance in maths, coding, and multi-turn dialogue compared to Qwen2.5 and QwQ.

What kind of tasks can I use Qwen3-4B for?

You can use it for coding assistance, problem-solving in maths and logic, creative writing, role-play, multilingual translation and integrating with external tools for task execution.

Does Qwen3-4B support multilingual use?

Yes, it supports over 100 languages and dialects, making it effective for cross-language communication and translation.

Which GPU should I use to run Qwen3-4B?

You can use the NVIDIA H100 PCIe GPU to run the Qwen3-4B model on Hyperstack.