====== Claude Opus 4.7 vs Opus 4.6 ======
**[[claude_opus_47|Claude Opus 4.7]]** and **Claude Opus 4.6** represent successive generations of [[anthropic|Anthropic]]'s flagship language model. Opus 4.7, launched in April 2026, introduces significant improvements in coding capabilities, vision processing, and reasoning while maintaining backward compatibility in pricing and API structure (([[https://news.smol.ai/issues/26-04-16-opus-47/|AI News - Claude Opus 4.7 vs Opus 4.6 (2026]])), ([[https://www.latent.space/p/ainews-anthropic-claude-opus-47-literally|Latent Space - Claude Opus 4.7 Release Analysis (2026)])). Opus 4.7 is positioned as substantially better at long-running work, instruction following, and self-verification compared to its predecessor. The system prompt has been significantly updated with new tool integrations, expanded child safety guidelines, and improved tool-using capabilities through the tool_search mechanism (([[https://simonwillison.net/2026/Apr/18/opus-system-prompt/#atom-entries|Simon Willison Blog - Claude Opus 4.7 (2026]])). Claude Opus 4.6, released on February 5, 2026, represented the prior generation and included less sophisticated tool-search capabilities and a less mature approach to child safety guidelines (([[https://simonwillison.net/2026/Apr/18/opus-system-prompt/#atom-entries|Simon Willison Blog (2026]])).

Opus 4.7 introduces new agent integrations including Chrome, Excel, and PowerPoint, along with improved handling of ambiguity through acting-over-asking directives and refined knowledge cutoff handling. ((Simon Willison Blog (2026))). In contrast, Opus 4.6 contained outdated language regarding political figures and relied on less sophisticated tool disambiguation mechanisms. ((Simon Willison Blog (2026))).

===== Pricing Structure =====
Both [[claude_opus_47|Claude Opus 4.7]] and Opus 4.6 maintain identical nominal pricing at **$5 per million input tokens** and **$25 per million output tokens**. However, a critical distinction emerges in token efficiency: Opus 4.7 implements a new tokenizer that consumes approximately **35% more tokens** to encode identical text compared to Opus 4.6. This tokenizer change effectively increases the real cost per unit of text processed, despite the published per-token rates remaining constant. Users comparing true operational expenses between versions must account for this [[tokenization|tokenization]] difference when evaluating total cost of ownership (([[https://www.theneurondaily.com/p/anthropic-shipped-opus-4-7-[[openai|openai]]))-countered|The Neuron - Anthropic Shipped Opus 4.7 (2026]])).

===== Performance Tier Structure =====
Opus 4.7 reorganizes the capability tier system to provide better granularity across effort levels. The model introduces a new **xhigh** tier at the top of the performance spectrum, expanding beyond the previous maximum tier available in Opus 4.6. This tier structure is designed such that lower-tier variants of Opus 4.7 outperform higher-tier variants of Opus 4.6—specifically, the 4.7-low tier demonstrates performance superior to the 4.6-medium tier, the 4.7-medium tier exceeds the 4.6-high tier, and the 4.7-high tier surpasses the 4.6-max tier (([[https://www.latent.space/p/ainews-[[anthropic|anthropic]]))-claude-opus-47-literally|Latent Space - Claude Opus 4.7 Release Analysis (2026)])). This architecture allows users to achieve comparable or superior results at lower computational expense compared to Opus 4.6.

===== Vision and Reasoning Capabilities =====
Opus 4.7 demonstrates substantial improvements in visual understanding and reasoning tasks. [[vision_reasoning|Vision reasoning]] performance increased from **69.1% to 82.1%**, representing a gain of approximately 13 percentage points on standardized benchmarks. This improvement reflects enhanced capabilities in interpreting visual content, extracting meaningful information from images, and reasoning about visual relationships (([[https://www.theneurondaily.com/p/anthropic-shipped-opus-4-7-[[openai|openai]]))-countered|The Neuron - Anthropic Shipped Opus 4.7 (2026]])).

Image processing specifications also expanded significantly. Opus 4.6 supported images up to approximately 800 pixels in maximum dimension, while Opus 4.7 extends this to **2,576 pixels**. This threefold increase in image resolution capacity enables the model to process higher-fidelity visual inputs, supporting more detailed analysis of photographs, diagrams, charts, and other visual materials (([[https://www.theneurondaily.com/p/anthropic-shipped-opus-4-7-[[openai|openai]]))-countered|The Neuron - Anthropic Shipped Opus 4.7 (2026]])).

===== Coding Performance Improvements =====
Opus 4.7 demonstrates substantial advancement in code-related benchmarks across multiple evaluation frameworks. **[[swe_bench|SWE-Bench]] Pro** shows approximately an 11 percentage point improvement compared to Opus 4.6, with Opus 4.7 achieving **64.3%** on this competitive programming benchmark focused on real-world software engineering tasks (([[https://news.smol.ai/issues/26-04-16-opus-47/|AI News - Claude Opus 4.7 vs Opus 4.6 (2026]])), ([[https://www.latent.space/p/ainews-[[anthropic|anthropic]]-claude-opus-47-literally|Latent Space - Claude Opus 4.7 Release Analysis (2026)])). This metric indicates enhanced capabilities in understanding complex codebases, generating syntactically and semantically correct code solutions, and handling sophisticated programming challenges.

On the **SWE-Verified** benchmark, which measures code correctness with stricter validation criteria, Opus 4.7 reaches **87.6%**, representing a 7 percentage point improvement and indicating robust handling of code generation tasks requiring precise syntax and logic (([[https://news.smol.ai/issues/26-04-16-opus-47/|AI News - Claude Opus 4.7 vs Opus 4.6 (2026]])), ([[https://www.latent.space/p/ainews-[[anthropic|anthropic]]-claude-opus-47-literally|Latent Space - Claude Opus 4.7 Release Analysis (2026)])). 

Terminal command generation and execution capabilities also improved measurably, with Opus 4.7 achieving **69.4%** on TerminalBench, a benchmark assessing the model's ability to generate and reason about shell commands.

===== See Also =====

  * [[claude_opus_4_7_vs_gemini_3_1_pro|Claude Opus 4.7 vs Gemini 3.1 Pro]]
  * [[opus_4_7_vs_mythos|Claude Opus 4.7 vs Claude Mythos]]
  * [[qwen_3_6_35b_a3b_vs_claude_opus_4_7|Qwen3.6-35B-A3B vs Claude Opus 4.7]]
  * [[claude_opus_vs_gpt_rosalind|Claude Opus 4.7 vs GPT Rosalind]]
  * [[opus_4_6|Opus 4.6]]

===== References =====