Artificial Analysis Launches Coding Agent Index v2.0, Claude Opus 5.5 Tops Ranking

On October 23, Artificial Analysis released Coding Agent Index v2.0, which evaluates models together with their agent harnesses across 290 tasks. It equally weights three benchmarks—software engineering, terminal use, and repository Q&A—and adds two new dimensions: per-task cost and token usage. The methodology and version history have been published alongside.

Confirmed

• On the overall leaderboard, Claude Opus 5.5 takes first place with a score of 61.7.
• The repository Q&A benchmark SWE-Atlas-QnA-AA still uses Scale AI's 124 repository Q&A questions, but rewrites 127 of the 1306 scoring rubric items; on this benchmark, Muse Wonder Full ranks first at 68.8%.
• Compared with v1.5, across the 21 configurations tested on both versions, the average score fell from 54.8 to 47.4, with 20 configurations declining—according to Artificial Analysis, mainly due to adjustments to Frontier-related benchmarks.

Why it matters

The index binds model capability to the agent harness in evaluation and introduces cost and token consumption dimensions, providing a stricter yardstick for measuring the overall cost-effectiveness of coding agents. The across-the-board score drop in v2.0 shows that tightening the methodology can significantly change how rankings look, so users comparing old and new leaderboards should be mindful of version differences.

2026-10-23 ~ 2026-10-23 · 6 related posts

• [source] Artificial Analysis launches Coding Agent Index v2.0: Claude Opus 5.5 leads at 61.7 — ArtificialAnlys · 2026-10-23
• SWE-Atlas-QnA-AA benchmark: Muse Wonder Full tops revised repo Q&A grading at 68.8% — ArtificialAnlys · 2026-10-23
• [source] Artificial Analysis launches Coding Agent Index v2.0 with lower scores across the board — ArtificialAnlys · 2026-10-23
• [source] Coding Agent Index v2.0 scores drop across the board: 20 of 21 configs decline — ArtificialAnlys · 2026-10-23

2 near-duplicate retellings: jffwng · ryanallred