Gemini 3.1 Pro Leads with 82.39 Points: 2026-10-13 Smoke Quick-Test Data Brief

On 2026-10-13, the YZ Index Smoke quick test covered 13 models, with Gemini 3.1 Pro ranking first for the day at 82.39 points. Smoke is a daily 10-question quick test, suitable for observing short-term signals; it is not equivalent to the conclusions of the Full weekly leaderboard.

This Smoke evaluation covered only two main leaderboard dimensions: code execution and material constraints. The main leaderboard formula is 0.55 × code execution + 0.45 × material constraints. Due to the small daily sample size, single-day scores are better used as monitoring signals rather than long-term conclusions about model capabilities.

Daily Ranking

RankModelMain LeaderboardCode ExecutionMaterial ConstraintsIntegrity
#1Gemini 3.1 Pro82.3991.771pass
#2GPT-o370.917565.9pass
#3Grok 470.917565.9warn
#4Doubao Pro69.117561.9pass
#5DeepSeek V4 Pro64.275081.7pass
#6GPT-6 Luna62.857548pass
#7GPT-6.1 Sol6158.364.3pass
#8Claude Sonnet 4.660.175072.6pass
#9GPT-5.559.9258.361.9pass
#10GPT-6 Astra59.9258.361.9pass
#11GPT-6 Sol59.847541.3pass
#12Claude Opus 4.759.455071pass
#13Gemini 2.5 Pro57.165065.9pass

Data Interpretation

In today's YZ Index Smoke quick test, Gemini 3.1 Pro ranked first with a main leaderboard score of 82.39; its 91.7 in code execution and 71 in material constraints form a clearly strong combination, and under the 0.55 weight, its code execution contribution stands out. GPT-o3 and Grok 4 tied at 70.91 on the main leaderboard, both showing a structure of 75 in code execution and 65.9 in material constraints; leading models overall rely on score momentum from the code execution side. DeepSeek V4 Pro is characterized by 81.7 in material constraints, and its main leaderboard score of 64.27 reflects a relative advantage on the material constraints side.

GPT-6 Astra fell 25.1 points on the main leaderboard, 38.7 in code execution, and 8.4 in material constraints; GPT-6.1 Sol fell 24 points on the main leaderboard, 38.7 in code execution, and 6 in material constraints; GPT-6 Sol fell 23 points on the main leaderboard, 19.8 in code execution, and 26.8 in material constraints; GPT-6 Luna fell 15.7 points on the main leaderboard, 22 in code execution, and 8 in material constraints; and Doubao Pro fell 15.6 points on the main leaderboard, 16.5 in code execution, and 14.4 in material constraints. All are significant single-day movements. These changes may stem from question sampling fluctuations or may reflect real degradation, requiring subsequent same-methodology run verification.

The Smoke quick test is a small-sample single-day signal. Current data only shows different combinations between code execution and material constraints among leading models, with no other anomalies observed. Interpretation remains restrained to avoid over-inference.

Main Changes

  • GPT-6 Astra: main leaderboard down 25.1 points, code execution -38.7, material constraints -8.4
  • GPT-6.1 Sol: main leaderboard down 24 points, code execution -38.7, material constraints -6
  • GPT-6 Sol: main leaderboard down 23 points, code execution -19.8, material constraints -26.8
  • GPT-6 Luna: main leaderboard down 15.7 points, code execution -22, material constraints -8
  • Doubao Pro: main leaderboard down 15.6 points, code execution -16.5, material constraints -14.4

Signals to Watch

  • No publishable anomalous signals were retained this time.

When reading this type of Smoke brief, focus on two questions: first, whether a model has repeatedly exposed the same type of weakness over multiple consecutive days; second, whether its integrity rating has moved from pass to warn or fail. Large single-day changes in execution or constraint scores may come from question sampling or may be early signals of real degradation, requiring subsequent run verification.


Data source: YZ Index | Run #375 | View raw data

This article is from Winzheng Index blog, translated in full by Winzheng (winzheng.com). Click here to view the original When republishing the translation, please credit the source. Thank you!