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# Claude Opus 4.6 led Vibe Code Bench at 57.6% in early 2026, 26 points above the lowest of eight models
- URL: https://aiadoption.org/data/vibe-code-bench-app-building/
- Published: 2026-10-19T16:06:38.000Z
- Updated: 2026-10-21T06:01:09.000Z
- Description: On Vibe Code Bench, which asks models to build complete web applications from a prompt, Claude Opus 4.6 (Nonthinking) scored 57.6% in early 2026. GLM 5.1, the lowest of the eight models shown, scored 31.5%.
- Author: Manu
- Tags: Data, AI Benchmarks, AI Coding, #chart, #ai-index-2026, #hub-benchmarks

57.6%

#1 of 8

Vibe Code Bench accuracy of Claude Opus 4.6 (Nonthinking), the highest of the eight models shown; GPT 5.2 scored 53.5%

Claude Opus 4.6 (Nonthinking)57.6%

GPT 5.253.5%

GLM 5.131.5%

## What the chart shows

Vibe Code Bench tests whether a model can take a prompt and deliver a working web application end to end, rather than assist with code. Claude Opus 4.6 without extended thinking led the eight models shown at 57.6%, ahead of GPT 5.2 and Claude Opus 4.6 with thinking (both 53.5%).

Scores fall to 48% for GPT 5.4 Mini, 37.9% for GPT 5.2 Codex and 31.5% for GLM 5.1, a spread of 26 percentage points. Even the leader falls short on more than four in ten tasks.

## Key numbers

| Measure                       | Value  |
| ----------------------------- | ------ |
| Claude Opus 4.6 (Nonthinking) | 57.57% |
| GPT 5.2                       | 53.50% |
| Claude Opus 4.6 (Thinking)    | 53.50% |
| GPT 5.4 Mini                  | 47.97% |
| GPT 5.2 Codex                 | 37.91% |
| GLM 5.1                       | 31.46% |

## How to read it

- The report text describes an earlier state of the leaderboard (a leader at 56.5%, GPT 5.3 Codex at 41.4%, several models below 15%); we use the figure’s data.
- “Thinking” and “Nonthinking” are the same model with and without extended reasoning.
- Scores are from Vals.ai’s Vibe Code Bench v1.1 leaderboard; the AI Index shows eight models.

**Source:** [Vals.ai](https://aiadoption.org/sources/#vals-ai), 2026, via the AI Index Report 2026 (Stanford HAI), figure 2.5.3: *Vibe Code Bench v1.1: accuracy*. Chart and text by AI Adoption.  
Numbers checked against the published data on 20 October 2026.  
[Download the data (CSV)](https://charts.aiadoption.org/ai-index/csv/vibe-code-bench-app-building.csv?ref=aiadoption.org) · [Cite this chart](#source)