Which Claude Model Should I Use? (2026)

Anthropic offers three Claude model tiers: Opus, Sonnet, and Haiku. Picking the wrong one costs you money, time, or quality. Opus handles complex reasoning but costs 15 times more than Haiku. Haiku responds in milliseconds but struggles with multi-step logic. Sonnet sits in the middle, good enough for most tasks at a reasonable price.

This guide gives you a concrete decision tree so you never have to guess again. For instant recommendations, try the Model Selector tool.

The Quick Decision Tree

Start here: What is the task?
├── Complex reasoning / architecture / debugging
│   └── Use Opus
│       Cost: $15/M input, $75/M output
│       Speed: 30-60 tokens/sec
│       When: System design, complex refactors, subtle bugs
│
├── Standard coding / writing / analysis
│   └── Use Sonnet
│       Cost: $3/M input, $15/M output
│       Speed: 60-90 tokens/sec
│       When: Feature implementation, code review, docs
│
└── Simple tasks / classification / extraction
    └── Use Haiku
        Cost: $0.25/M input, $1.25/M output
        Speed: 150+ tokens/sec
        When: Formatting, simple edits, data extraction

Detailed Task-to-Model Mapping

Use Opus When

Architecture decisions. Designing a system that handles 10,000 concurrent WebSocket connections requires understanding multiple layers: connection pooling, message routing, backpressure, and failure modes. Opus excels at holding this complexity.

Complex debugging. When a bug spans multiple files, involves race conditions, or requires understanding subtle type system interactions, Opus finds the root cause faster. Sonnet often identifies the symptom but misses the underlying issue.

Multi-file refactoring. Renaming a core abstraction that touches 30 files requires understanding how the change propagates. Opus tracks these dependencies accurately.

Code review with context. Reviewing a PR that changes authentication flow requires understanding security implications that Sonnet may miss.

Use Sonnet When

Feature implementation. Building a standard CRUD endpoint, adding a form component, or writing a utility function. These tasks have clear patterns and Sonnet handles them reliably.

Code generation from specs. Given a clear specification, Sonnet generates correct implementations. The task complexity is in the scope, not the reasoning depth.

Documentation writing. API docs, README updates, and inline comments. Sonnet produces high-quality technical writing at 5x lower cost than Opus.

Test writing. Unit tests and integration tests follow patterns. Sonnet generates comprehensive test suites that cover edge cases.

Standard code review. Reviewing straightforward PRs for style, correctness, and test coverage. Sonnet catches most issues.

Use Haiku When

Code formatting. Reformatting imports, converting between coding styles, or applying consistent naming conventions. These are pattern-matching tasks where Haiku matches Opus quality.

Data extraction. Pulling structured data from logs, converting file formats, or parsing configuration files.

Simple edits. Fixing typos, updating version numbers, renaming variables within a single file.

Classification. Categorizing issues, triaging bugs, or labeling code changes by type.

Boilerplate generation. Creating repetitive code that follows a strict template with minimal decision-making.

Cost Comparison: Real Scenarios

Here is what each model costs for common tasks, assuming average token counts:

Task Tokens Opus Cost Sonnet Cost Haiku Cost
Implement REST endpoint ~8K $0.72 $0.14 $0.012
Debug async race condition ~15K $1.35 $0.27 $0.023
Write 20 unit tests ~12K $1.08 $0.22 $0.018
Refactor auth module ~25K $2.25 $0.45 $0.038
Format 50 import statements ~3K $0.27 $0.05 $0.005

For the formatting task, all three models produce identical results, so Haiku at $0.005 is the obvious choice. For the auth refactor, Opus at $2.25 prevents mistakes that could take hours to debug.

The 80/15/5 Rule

Most teams find their workload splits roughly:

  • 80% Sonnet — Standard development tasks
  • 15% Haiku — Simple, repetitive tasks
  • 5% Opus — Complex reasoning and critical decisions

This distribution keeps costs low while maintaining quality where it matters. Teams that use Opus for everything spend 5-10x more than necessary. Teams that use only Haiku miss critical bugs and produce lower-quality architecture.

Try It Yourself

Choosing the right model for every task is mentally taxing, especially when you are deep in a coding session. The Model Selector tool takes your task description and recommends the optimal Claude model based on complexity, cost, and speed requirements. It removes the guesswork so you can focus on the actual work.

When to Override the Decision Tree

The decision tree works for 90 percent of cases. Override it when:

Latency matters more than quality. In production systems where Claude responds to users in real-time, Haiku’s sub-second response time may be worth the quality tradeoff even for moderately complex tasks.

Budget is exhausted. If your monthly API budget is running low, drop from Opus to Sonnet for everything and accept slightly lower quality on complex tasks. Sonnet handles 85-90 percent of what Opus handles at one-fifth the cost.

Batch processing. For processing hundreds or thousands of items, the cost multiplier matters enormously. A task that costs $0.05 with Haiku costs $3.00 with Opus. At 10,000 items, that is $500 versus $30,000.

Prototyping. When exploring ideas and expecting to throw away code, use Haiku for speed and cost. Switch to Sonnet or Opus when building production code.

Model Capabilities at a Glance

Capability Opus Sonnet Haiku
Complex reasoning Excellent Good Limited
Code generation Excellent Very Good Good
Following instructions Excellent Very Good Good
Speed (tokens/sec) 30-60 60-90 150+
Context window 200K 200K 200K
Tool use Excellent Very Good Good
Cost efficiency Low Medium High

Know your costs → Use our Claude Code Cost Calculator to estimate your monthly spend.

Estimate tokens → Calculate your usage with our Token Estimator.

Frequently Asked Questions

Does Claude Code let me switch models mid-session?

Yes. You can change models during a Claude Code session. Use this to start complex tasks with Opus for the design phase, then switch to Sonnet for implementation. Your conversation context carries over.

Is Sonnet good enough for most coding tasks?

Yes. Sonnet handles approximately 80 percent of coding tasks with quality comparable to Opus. The gap appears mainly in complex multi-step reasoning, subtle bug diagnosis, and system architecture decisions.

When should I use Haiku instead of Sonnet for coding?

Use Haiku for tasks where the pattern is clear and does not require creative problem-solving: formatting, simple refactors, boilerplate generation, and data transformation. The cost savings compound significantly for high-volume tasks.

How do I measure if I picked the right model?

Track two metrics: task completion quality and cost per task. If Haiku produces the same quality output as Sonnet for a task type, use Haiku. If Sonnet fails to catch bugs that Opus would, upgrade that task category to Opus.