Run Qwen3 Coder on Google Colab with Free GPU

Run Qwen3 Coder on Google Colab with Free GPU

Introduction: No Hardware? No Problem.

Want to explore Qwen3’s powerful coding abilities but don’t have a high-end GPU?

Use Google Colab to:

  • Run Qwen3-Coder (7B/14B models)

  • Access a GPU for free

  • Try agentic coding workflows

  • No installation required on your machine

This guide walks you through setting up Qwen3-Coder in Colab using Transformers + Hugging Face.


1. Open Google Colab

Go to https://colab.research.google.com
Click "New Notebook", then follow these steps.


2. Enable Free GPU Runtime

In the menu:
RuntimeChange runtime type → Set GPU
(Usually a Tesla T4 or L4 on free tier)


3. Install Required Libraries

Run this in a code cell:

python
!pip install transformers accelerate bitsandbytes -q

4. Load Qwen3-Coder Model

You can choose:

  • Qwen/Qwen1.5-7B-Chat

  • Qwen/Qwen1.5-14B-Chat

  • Or any base/instruct variant

python
from transformers import AutoTokenizer, AutoModelForCausalLM model_id = "Qwen/Qwen1.5-7B-Chat" tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained( model_id, device_map="auto", trust_remote_code=True, load_in_4bit=True )

5. Run a Coding Prompt

python
prompt = ( "<|im_start|>system\nYou are a helpful Python coding assistant.<|im_end|>\n" "<|im_start|>user\nWrite a Python script that sorts a list of numbers using bubble sort.<|im_end|>\n" "<|im_start|>assistant\n" ) inputs = tokenizer(prompt, return_tensors="pt").to("cuda") outputs = model.generate(**inputs, max_new_tokens=300) print(tokenizer.decode(outputs[0]))

✅ You’ll get clean, agentic code output—similar to ChatGPT Code Interpreter.


6. Optional: Add Tool Use or Function Calling

Qwen3 models support:

  • JSON output (with correct prompt formatting)

  • Shell/REPL-style code generations

  • Function-call-like formatting

python
prompt = ( "<|im_start|>system\nOnly respond in JSON. No extra text.<|im_end|>\n" "<|im_start|>user\nReturn current datetime in Python code format.<|im_end|>\n" "<|im_start|>assistant\n" )

7. Notes on Colab Limitations

Limitation Workaround
Timeout after 90 min Save checkpoints to Google Drive
RAM capped at ~12GB Use Qwen3 7B model or 4-bit loading
Storage is temporary Push code to GitHub or Drive

Want more power? Upgrade to Colab Pro or use HF Spaces with a GPU.


Conclusion: Qwen3-Coder Anywhere, Anytime

Even with just a browser:

  • Run powerful LLM coding models

  • Explore agentic instructions

  • Use free GPU from Colab

Qwen3-Coder makes high-quality code generation open, fast, and cost-free.


Resources



Qwen3 Coder - Agentic Coding Adventure

Step into a new era of AI-powered development with Qwen3 Coder the world’s most agentic open-source coding model.