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AI Code Review Showdown: Anthropic's Claude vs IBM's Granite

Compare Anthropic's Claude 3.7 Sonnet and IBM's Granite 3.2 8B Instruct models for Python code review tasks in both reasoning and non-reasoning modes. This lab evaluates how these hybrid reasoning models perform when analyzing syntax errors, algorithms, authentication systems, and architecture. Discover which model delivers better accuracy, speed, and cost-efficiency for different coding scenarios. Learn when reasoning mode provides advantages over non-reasoning mode and identify optimal use cases for each approach based on comprehensive performance metrics.

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Guided Project

Skills Network

At a Glance

Compare Anthropic's Claude 3.7 Sonnet and IBM's Granite 3.2 8B Instruct models for Python code review tasks in both reasoning and non-reasoning modes. This lab evaluates how these hybrid reasoning models perform when analyzing syntax errors, algorithms, authentication systems, and architecture. Discover which model delivers better accuracy, speed, and cost-efficiency for different coding scenarios. Learn when reasoning mode provides advantages over non-reasoning mode and identify optimal use cases for each approach based on comprehensive performance metrics.

Imagine you're writing code, whether it's your first Python script or a complex application. You need AI assistance—for debugging, optimization, or architectural advice—but with so many models available, how do you choose the right one?

AI coding assistants like Claude 3.7 Sonnet and IBM Granite 3.2 8B Instruct promise to help, but their abilities vary. Does reasoning mode actually improve suggestions? Is one model better for beginners versus complex projects? In this hands-on lab, you'll test these models across four practical coding tasks—from basic syntax checks to system design—to see which AI truly elevates your development process. With the Generative AI Classroom, compare models side-by-side—no setup, no fees, no guesswork. Just log in, run experiments, and discover which AI best supports your coding journey.

Project Overview

This lab benchmarks Claude 3.7 Sonnet vs. IBM Granite 3.2 8B Instruct across coding tasks of increasing complexity:
1️⃣ Basic Code Review (syntax errors, style fixes)
2️⃣ Algorithm Analysis (time/space complexity optimizations)
3️⃣ System Design (authentication flows, architecture patterns)
4️⃣ End-to-End Feedback (readability, maintainability, scalability)

You’ll evaluate them on three key metrics:
Speed – Response times for quick iterations
Cost – Value per query at scale
Accuracy – Error detection and suggestion quality

What You’ll Learn

By completing this lab, you will:
  • Compare reasoning vs. standard modes for coding tasks
  • Identify which model excels at beginner support vs. expert-level design
  • Learn prompting techniques to get better coding help
  • Gain hands-on experience with AI-assisted development

Who Should Do This Lab?

Perfect for anyone who codes—no matter your level:
  • Beginners seeking AI tutoring for fundamentals
  • Intermediate devs optimizing algorithms
  • Senior engineers evaluating AI for architecture reviews
  • Educators comparing AI teaching tools
No advanced skills needed—start with simple code and progress at your pace.

What You Need

A browser (Chrome/Firefox/Safari etc.)
Basic coding awareness (any language)
Curiosity—test prompts and draw conclusions!

Zero installations—everything runs in your browser. By the end, you’ll know whether Claude’s detailed analysis or Granite’s quick feedback better matches your needs—and how to leverage both effectively.

Estimated Effort

30 Minutes

Level

Beginner

Skills You Will Learn

Artificial Intelligence, Generative AI, Granite, LLM, Prompt Engineering, Python

Language

English

Course Code

GPXX0LVJEN

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