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Opus 4.7 shipped in April 2026 with a bigger thinking budget and a 1M-token window at standard prices. Here is the architecture, the pricing math, and when the premium is actually worth it.
Anthropic released Claude Opus 4.7 on April 16, 2026. The headline was not a new benchmark — it was that Opus, which had cost $15/$75 per million tokens on earlier generations, now ships at $5 in / $25 out with a 1M token context window. That is standard Sonnet-tier pricing for a flagship model, and it changes which tasks are cost-justified on Opus.
When you enable extended thinking, Claude spends hidden reasoning tokens before emitting the answer. You set a budget; Claude spends up to that budget. The bigger the budget, the deeper the search over approaches. Opus 4.7 handles budgets of tens of thousands of tokens gracefully; Sonnet starts to lose coherence at that scale.
| Dimension | Opus 4.7 without thinking | Opus 4.7 with thinking (8k budget) | Opus 4.7 with thinking (32k budget) |
|---|---|---|---|
| Latency | Similar to Sonnet | +10-20s | +1-3 minutes |
| Input cost impact | Same | Same | Same (input is just the prompt) |
| Output cost impact | Normal | +8k hidden tokens billed | +32k hidden tokens billed |
| Quality lift | Baseline | Meaningful on hard math/code | Decisive on research-grade problems |
| Right for | Everyday work, summarization | Complex debugging, multi-file refactor | Scientific reasoning, long-horizon agents |
from anthropic import Anthropic client = Anthropic() resp = client.messages.create( model="claude-opus-4-7", max_tokens=8192, thinking={ "type": "enabled", "budget_tokens": 16000 }, messages=[ {"role": "user", "content": "Given the attached 400-page regulatory filing, identify every section that conflicts with the EU AI Act provisions on high-risk systems."} ] ) # Inspect what Claude was thinking (optional, advanced) for block in resp.content: if block.type == "thinking": pass # hidden reasoning, not shown to end user elif block.type == "text": print(block.text) print(resp.usage) # input_tokens, output_tokens, thinking_tokens separateThe thinking block is part of the response but typically not shown to the end user. You can log it for audit, but never paste it back as context — it is one-shot reasoning.The right question is not 'can I afford Opus with extended thinking?' — it is 'can I afford to be wrong on this task?'
— Common framing from Anthropic's solutions engineers
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-model-claude-opus-reasoning-creators
What is the main idea of "Claude Opus 4.7 — when extended thinking earns its cost"?
Which concept is most central to "Claude Opus 4.7 — when extended thinking earns its cost"?
Which use of AI fits this topic best?
What should a careful learner remember about "You pay for the hidden tokens"?
You want to use AI after this lesson. What is the safest next step?
How should AI output about Claude Opus 4.7 be treated?
Name one way to verify an AI answer about Claude Opus 4.7.
Which action would help you apply "Claude Opus 4.7 — when extended thinking earns its cost" responsibly?