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Which Claude Model Should I Use: Haiku, Sonnet, or Opus?

Cowrie
Cowrie
Dev @ Bswen

Purpose

This post shows how to choose between Claude Haiku, Sonnet, and Opus models. The key point is matching model capabilities to task complexity to optimize both cost and quality.

The Problem

When I first started using Claude Code, I had one burning question: Which model should I use for what task?

I saw options for Haiku, Sonnet, and Opus. Without clear guidance, I defaulted to the most powerful model for everything. My costs climbed quickly. Then I tried using only the cheapest model and quality suffered.

I needed a practical guide. After reading through Reddit discussions and testing each model extensively, I found a clear pattern.

The Short Answer

Model Selection Quick Reference
Use Haiku for: Research, exploration, small predictable tasks
Use Sonnet for: Daily coding, feature implementation, debugging
Use Opus for:  Architecture decisions, complex planning, critical reviews

This matches what one Reddit user with 186 upvotes said:

“Keep Claude Opus off unless you really, really, REALLY need it. Use Haiku more often.”

Another user added:

“For predictable, small tasks where high hallucination is okay, Haiku is the tool of choice. Opus is best for deep thinking tasks that need analysis and planning.”

Model Comparison

Here’s how I break down the three models:

Claude Model Comparison
+--------+-----------+------------------+------------------+
| Model  | Cost      | Best For         | Avoid For        |
+--------+-----------+------------------+------------------+
| Haiku  | Lowest    | Research,        | Complex logic,   |
|        |           | cleanup, simple  | architecture,    |
|        |           | refactoring      | critical code    |
+--------+-----------+------------------+------------------+
| Sonnet | Medium    | Daily coding,    | Very complex     |
|        |           | features,        | planning,         |
|        |           | debugging        | novel problems   |
+--------+-----------+------------------+------------------+
| Opus   | Highest   | Architecture,    | Simple tasks,     |
|        |           | planning,        | exploration,      |
|        |           | critical reviews | routine work      |
+--------+-----------+------------------+------------------+

When to Use Haiku

Haiku handles 90% of what Sonnet can do at 3x lower cost. I use Haiku for:

1. Research and Exploration

Haiku Use Cases: Research
- Searching codebases for patterns
- Reading documentation
- Understanding existing code structure
- Initial problem investigation

The key insight: Haiku excels when I don’t know exactly what I’m looking for. If I’m exploring a new codebase or researching a technology, Haiku gives me quick answers without burning expensive tokens.

2. Simple, Predictable Tasks

Haiku Use Cases: Predictable Tasks
- Renaming variables across files
- Formatting code consistently
- Adding logging statements
- Writing boilerplate code
- Generating test data

These tasks have clear inputs and outputs. Haiku handles them reliably.

3. Code Cleanup

I use Haiku for end-of-day cleanup:

  • Removing unused imports
  • Organizing file structure
  • Adding missing type annotations
  • Fixing linting errors

The Reddit discussion highlighted this point: Haiku is perfect for “predictable, small tasks where high hallucination is okay.” Why? Because cleanup tasks are easily verifiable. If Haiku makes a mistake, I catch it immediately.

When to Use Sonnet

Sonnet is my daily workhorse. I use it for:

1. Feature Implementation

Sonnet Use Cases: Features
- Building new components
- Writing API endpoints
- Implementing business logic
- Creating database schemas

Sonnet balances cost and capability. For most coding tasks, Sonnet produces quality output without the premium cost of Opus.

2. Debugging

When something breaks, Sonnet is my first call:

  • Analyzing error messages
  • Tracing through call stacks
  • Identifying root causes
  • Proposing fixes

Sonnet understands context well enough to debug most issues effectively.

3. Code Review

I use Sonnet for initial code reviews:

  • Checking coding standards
  • Identifying potential bugs
  • Suggesting improvements
  • Ensuring test coverage

When to Use Opus

Opus is for deep thinking. The Reddit user was blunt: “Keep Claude Opus off unless you really, really, REALLY need it.”

I reserve Opus for:

1. Architecture Decisions

Opus Use Cases: Architecture
- System design from scratch
- Major refactoring plans
- Technology selection
- Performance optimization strategies

These decisions have lasting impact. The extra cost of Opus pays off when the architecture needs to be right.

2. Complex Planning

When I start a significant feature, Opus helps me:

  • Break down the work into phases
  • Identify dependencies and risks
  • Consider edge cases
  • Plan testing strategy

3. Critical Code Reviews

For security-sensitive code or core business logic, I use Opus to:

  • Review for security vulnerabilities
  • Identify subtle bugs
  • Evaluate algorithmic complexity
  • Check for race conditions

A Practical Workflow

I’ve developed a daily workflow that optimizes model usage:

Daily Model Workflow
Morning (Planning):
+------------------+------------------+
| Task             | Model            |
+------------------+------------------+
| Review roadmap   | Opus             |
| Plan features    | Opus             |
| Architecture     | Opus             |
+------------------+------------------+


Midday (Implementation):
+------------------+------------------+
| Task             | Model            |
+------------------+------------------+
| Write code       | Sonnet           |
| Debug issues     | Sonnet           |
| Write tests      | Sonnet           |
+------------------+------------------+


Afternoon (Cleanup):
+------------------+------------------+
| Task             | Model            |
+------------------+------------------+
| Refactor         | Haiku            |
| Add docs         | Haiku            |
| Cleanup imports  | Haiku            |
+------------------+------------------+

This workflow matches model capability to task complexity throughout the day.

Common Mistakes

I made several mistakes when learning model selection:

1. Using Opus for Everything

My first week, I used Opus for all tasks. Costs were 5x higher than necessary. The output wasn’t better for simple tasks.

2. Avoiding Opus Completely

Then I swung the other direction. I never used Opus, even for complex architecture decisions. My designs suffered.

3. Ignoring Context Window

Different models have different context limits. When I hit the limit with Haiku, I switched to Opus. The right answer was to simplify the task or use Sonnet’s larger context window.

How I Decide Now

I use this simple decision tree:

Model Selection Decision Tree
1. Is this task predictable with clear inputs/outputs?
   → YES: Use Haiku
   → NO: Continue


2. Is this a standard coding task (feature, bug fix, review)?
   → YES: Use Sonnet
   → NO: Continue


3. Is this a complex decision with lasting impact?
   → YES: Use Opus
   → NO: Default to Sonnet

Summary

In this post, I explained how to choose between Claude Haiku, Sonnet, and Opus. The key point is matching model capability to task complexity.

Remember:

  • Haiku: 90% of Sonnet’s capability at 3x cost savings
  • Sonnet: Daily workhorse for most coding tasks
  • Opus: Reserve for deep thinking and critical decisions

Next time you start a task, ask: “Do I need the smartest model for this, or will a cheaper one do?” Your budget will thank you.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!

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