Gemini 3.1 Pro Leads with 90.36: 2026-10-31 Smoke Rapid Test Data Brief

The 2026-10-31 YZ Index Smoke rapid test covers 14 models, and Gemini 3.1 Pro ranked first for the day with 90.36 points. Smoke is a daily 10-question rapid test, suitable for observing short-term signals and not equivalent to conclusions from the weekly Full leaderboard.

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

Daily Ranking

RankModelMain LeaderboardCode ExecutionMaterial ConstraintsIntegrity
#1Gemini 3.1 Pro90.369485.9pass
#2Doubao Pro88.4881.597pass
#3GPT-6 Astra86.449477.2pass
#4Claude Sonnet 4.685.189474.4pass
#5DeepSeek V4 Pro84.879473.7pass
#6GPT-6 Luna84.19472pass
#7GPT-6.1 Sol84.19472pass
#8Grok 483.839471.4pass
#9Claude Opus 4.782.9569100pass
#10Gemini 2.5 Pro78.1181.374.2pass
#11GPT-o377.696988.3pass
#12GPT-6 Sol74.1466.883.1pass
#13GPT-5.570.356972pass
#14GLM-4.645.597213.3pass

Data Interpretation

In today's YZ Index Smoke rapid test, Gemini 3.1 Pro ranked first with a main leaderboard score of 90.36; its combination of 94 in code execution and 85.9 in material constraints shows relatively balanced performance. Doubao Pro had a main leaderboard score of 88.48, with code execution at 81.5 and material constraints at 97, showing a stronger material-constraints profile. Leading models such as GPT-6 Astra (main leaderboard 86.44, code execution 94, material constraints 77.2) and Claude Sonnet 4.6 (main leaderboard 85.18, code execution 94, material constraints 74.4) generally relied on a high code-execution level of 94 to support their overall scores.

DeepSeek V4 Pro gained 38.5 points on the main leaderboard and 69 points in code execution; Gemini 2.5 Pro gained 31 points on the main leaderboard and 57 points in code execution; Doubao Pro gained 27 points on the main leaderboard, 36.7 points in code execution, and 15.1 points in material constraints; Grok 4 gained 24.8 points on the main leaderboard and 45.9 points in code execution. These models' significant gains mainly came from improvements in code execution; GPT-6 Sol fell 16.4 points on the main leaderboard and 33.2 points in code execution, a clear decline.

Anomalous signals such as GPT-6 Luna's material constraints dropping sharply by 15.9 points, GPT-6 Sol's main leaderboard score dropping sharply by 16.4 points, GPT-5.5's main leaderboard score dropping sharply by 8.8 points, and GLM-4.6's material constraints dropping sharply by 43.6 points may stem from question sampling fluctuations or real degradation and require follow-up runs for confirmation; Qwen3 Max was not ranked due to incomplete data. As a small-sample single-day signal, Smoke should be interpreted with restraint.

Key Changes

  • DeepSeek V4 Pro: Main leaderboard up 38.5 points, code execution +69 points, integrity warn→pass
  • Gemini 2.5 Pro: Main leaderboard up 31 points, code execution +57 points
  • Doubao Pro: Main leaderboard up 27 points, code execution +36.7 points, material constraints +15.1 points
  • Grok 4: Main leaderboard up 24.8 points, code execution +45.9 points
  • GPT-6 Sol: Main leaderboard down 16.4 points, code execution -33.2 points

Signals to Watch

  • GPT-6 Luna: Material constraints dropped sharply by 15.9 points
  • GPT-6 Sol: Main leaderboard dropped sharply by 16.4 points
  • GPT-5.5: Main leaderboard dropped sharply by 8.8 points
  • GLM-4.6: Material constraints dropped sharply by 43.6 points
  • Qwen3 Max: Incomplete data (missing several evaluation dimensions; API failure/timeout), automatically queued for rerun, not ranked in this period

When reading this type of Smoke brief, focus on two questions: first, whether a model has exposed the same type of weakness for multiple consecutive days; second, whether its integrity rating has moved from pass to warn or fail. Large single-day changes in code-execution or material-constraint scores may come from question sampling or may be an early signal of real degradation, requiring follow-up runs for confirmation.


Data source: YZ Index | Run #404 | 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!