Why Claude 4 Sonnet is the Sweet Spot for Indie Builders

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Claude 4 just became the world's best coding AI.

I spent 6 hours testing both models with real tasks.

What I discovered might save you hundreds in token costs.

Let’s dive right into it!

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First, let me explain what just happened.

Anthropic released two models this Thursday: Claude 4 Opus and Claude 4 Sonnet. This is huge because we haven't seen an Opus model since Claude 3. They skipped it entirely for versions 3.5 and 3.7.

Here's the hierarchy:

• Opus = The flagship. Biggest brain, highest cost, maximum power

• Sonnet = The workhorse. Medium size, balanced cost, solid performance

• Haiku = The speed demon. Smallest, cheapest, fastest (not released yet for v4)

The Tale of Two Models: Why Sonnet Beats Opus for Most of Us

Both models crush every competitor on coding benchmarks but here's the detail that you need to know!

Claude 4 Sonnet (the "medium" model) actually outperformed Claude 4 Opus (the flagship) on the main coding benchmark (SWE-bench verified).

This highlights the fact that “smaller” can win when tuned for dev work and Anthropic really excels at crafting models for devs.

Let me break this down with the official numbers:

When to choose Sonnet:

• ✅ 5× cheaper ($3 vs $15 per million input tokens)

• ✅ Faster responses for quick iterations

• ✅ 72.7% on SWE-bench (vs Opus at 72.5% - yes, higher!)

• ✅ Perfect for: bug fixes, feature builds, code reviews

When to choose Opus:

• ✅ Maximum reasoning power for complex problems

• ✅ Better at sustained multi-hour tasks (7+ hours reported) - I don’t know who’s able to afford that 🙈

• ✅ Superior memory capabilities with "memory files"

• ✅ Stronger performance on research and scientific tasks

• ✅ Perfect for: system design, complex debugging, agent workflows

The reality check: Sonnet handles 95% of daily coding tasks and beats Opus on core coding benchmarks.

The big tech companies agree as GitHub is switching their new Copilot coding agent to Claude Sonnet 4.

The State-of-the-art Model Comparison

Here's how Claude 4 stacks up against the competition on tasks that actually matter to indie builders:

Translation for solopreneurs:

• Need reliable agents? → Claude Sonnet 4

• Building frontend apps? → Claude Sonnet 4 or Gemini 2.5 Pro

• Working with huge codebases? → GPT-4.1 or Gemini (for the 1M context)

• On a tight budget? → GPT-4.1 (best performance per dollar)

• Need maximum reliability? → Avoid Claude Opus 4 until uptime improves

The Hidden Cost Trap That's Breaking AI Budgets

Here's where things get scary. Thinking modes can explode your costs by 14-150×

Real example from Artificial Analysis benchmark:

• Standard Claude 3.7: $109 to run benchmark tests

• Claude 3.7 with thinking: $1,485 for the same tests

A roughly 14x increase:

Why? "Thinking tokens" are invisible reasoning steps the AI does before giving you an answer. You pay for every single one—even though you never see them.

The hidden multipliers:

• Gemini Flash reasoning: 150× cost increase

• Claude thinking: 14× cost increase

Workflow Win You Can Use Today - The Memory File Trick

Claude 4 (especially Opus) now automatically creates "memory files"—markdown or text files that store key information about your codebase across sessions.

How it works: Give Claude local file access, and it starts maintaining notes about your project's architecture, coding standards, and important decisions.

Prompt: "Analyze this codebase and create a memory file. Include key architecture decisions, coding patterns, and any important context for future sessions."

Result: No more re-explaining your entire setup every conversation. Claude remembers your preferences and project context.

Here’s the example from Anthropic - they used the Memory File Trick when teaching Claude Opus to play Pokémon!

Time to Wrap it Up!

It’s time for you to take action!

Pick ONE coding task you've been putting off and feed it to Claude 4 Sonnet.

What's your biggest coding bottleneck right now?

Hit reply and tell me, I read every response.