Claude Opus 4.7 vs. Sonnet 4.6 — which Claude to pick

Opus is the flagship, Sonnet is the workhorse. Here is the five-minute decision tree for when to pay 2x more for Opus and when Sonnet handles it.

25 min · Reviewed 2026

Two Claudes, one question

Open the Anthropic model picker and you will see Opus 4.7 at the top and Sonnet 4.6 right under it. Both have a 1 million token context window, both handle vision, both run extended thinking. So why is Opus five times more expensive per output token? The honest answer: Opus earns that premium on a small slice of tasks. For the other 80% of your work, Sonnet is the right call.

What you are actually paying for

Dimension	Claude Opus 4.7	Claude Sonnet 4.6
API price	$5 in / $25 out per M tokens	$3 in / $15 out per M tokens
Context window	1,000,000 tokens	1,000,000 tokens
Extended thinking	Yes, deeper budget	Yes
Release date	April 16, 2026	2025
Best at	multi-file refactors, legal briefs, tough coding agents	everyday chat, code review, document QA
Speed	Slower per token	Faster per token

Reach for Opus when

You need to refactor code that spans 5+ files and depends on subtle invariants
You are drafting a legal brief, policy memo, or regulatory filing where mistakes cost real money
You are pushing a long-horizon agent (Claude Code on a complex branch, auto-PR generation)
You are analyzing a 500-page report and the answer matters for a real decision

Sonnet is enough when

Customer-support chatbot answering product questions
Daily email drafts, meeting notes, summaries
Code review on single files or small PRs
Routine document Q&A where citations matter more than depth

The API call looks the same

from anthropic import Anthropic client = Anthropic() # Opus for a hard coding job opus_reply = client.messages.create( model="claude-opus-4-7", max_tokens=4096, thinking={"type": "enabled", "budget_tokens": 8000}, messages=[{"role": "user", "content": "Refactor this multi-file auth module"}], ) # Sonnet for everyday chat — same shape, cheaper sonnet_reply = client.messages.create( model="claude-sonnet-4-6", max_tokens=1024, messages=[{"role": "user", "content": "Summarize this meeting transcript."}], )The only difference is the model string — swap when cost matters.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-model-claude-opus-vs-sonnet-builders

What is the main idea of "Claude Opus 4.7 vs. Sonnet 4.6 — which Claude to pick"?
1. Opus is the flagship, Sonnet is the workhorse. Here is the five-minute decision tree for when to pay 2x more for Opus and when Sonnet handles it.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Claude Opus 4.7 vs. Sonnet 4.6 — which Claude to pick"?
1. Claude Sonnet 4.6
2. Claude Opus 4.7
3. extended thinking
4. context window
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. You need to refactor code that spans 5+ files and depends on subtle invariants
4. Use the first answer without checking it
What should a careful learner remember about "The 2x-5x rule"?
1. Use AI to draft or organize ideas about Claude Opus 4.7, then verify before acting.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use the AI answer as a draft, then check it against a reliable source.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about Claude Opus 4.7 be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about Claude Opus 4.7.
Which action would help you apply "Claude Opus 4.7 vs. Sonnet 4.6 — which Claude to pick" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Use the first answer without checking it
4. You are drafting a legal brief, policy memo, or regulatory filing where mistakes cost real money

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