I Tested Claude Opus 4.7 vs 4.6 on 7 Real Tasks: The Default Setting Swap That Quietly Ends the…

2026-04-17 · Source: Towards AI - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Advanced, quick

Summary

Anthropic has released Claude Opus 4.7 to its API, Amazon Bedrock, Google Vertex AI, and Microsoft Foundry, priced identically to its predecessor at $5 per million input tokens and $25 per million output tokens. This release follows widespread developer accusations of "AI shrinkflation" regarding Opus 4.6, with analysis of 6,852 Claude Code session files and over 234,000 tool calls suggesting a sharp regression in complex engineering tasks. Initial testing of Opus 4.7 against 4.6 on seven identical tasks revealed that the new model successfully solved four problems that Opus 4.6 could not, a finding corroborated by Anthropic's internal 93-task benchmark. A significant, unannounced change is that Opus 4.7's default effort level silently shifted from "medium" to "high."

Key takeaway

For NLP Engineers and CTOs evaluating Claude models for complex engineering workloads, Opus 4.7 addresses critical performance regressions reported in Opus 4.6. You should prioritize upgrading to Opus 4.7 to leverage its enhanced problem-solving capabilities and be aware that its default "effort level" has changed from "medium" to "high," which may influence resource consumption or response quality in existing integrations.

Key insights

Claude Opus 4.7 resolves prior performance regressions and improves problem-solving capabilities over Opus 4.6.

Principles

• Model performance can fluctuate across versions.
• Default settings significantly impact model behavior.

In practice

• Test new model versions against specific use cases.
• Verify default configuration changes in model updates.

Topics

• Claude Opus 4.7
• AI Performance Benchmarking
• AI Model Pricing
• AI Shrinkflation
• Model Configuration

Best for: NLP Engineer, CTO, VP of Engineering/Data, AI Engineer, Machine Learning Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards AI - Medium.