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In today's Smoke evaluation, Gemini 2.5 Pro lost 22.6 points on the mainboard, with core execution dropping from 100 to 95 and material constraints slightly declining. The engineering judgment dimension collapsed from 66.7 to 30, and task expression fell from 50 to 10, signaling deeper issues beyond normal fluctuation.
In the latest Smoke quick test, 文心一言4.5 posted a deeply split report: the main score edged up, but its integrity rating dropped directly from pass to fail. This change is not an isolated incident but a concentrated manifestation of severe multidimensional volatility.
In today's Smoke 10-question quick test, the Gemini series suffered major declines on the main leaderboard, while Claude Sonnet 4.6 claimed the top spot with 97.5 points. Domestic models also showed strong gains, but Wenxin Yiyan 4.5 was directly marked as Fail.
Claude Opus 4.7's main ranking in today's Smoke evaluation dropped from 93.48 to 70.93, a single-day decline of 22.6 points. The code execution dimension plummeted from a perfect 100 to 50, the key driver of this drop.
In today's Smoke test, 豆包Pro's Material Constraint score dropped from 95 to 79.8, a single-day decline of 15.2 points, causing the main ranking to fall from 97.75 to 90.91. While other side dimensions improved, the anomaly is likely due to question sampling rather than permanent degradation, but continued monitoring is recommended.
In Smoke's latest 10-question quick test, execution weaknesses of AI models were laid bare. Grok 4 reached the top with 97.44 points, while GPT-o3's main leaderboard score dropped 28.1 points from 94.53 to 66.43.
The same classic SQL problem of consecutive logins split 11 mainstream models into two camps: 8 gave complete correct answers, and 3 completely collapsed.
When asked to rank reasons for a two-week project delay, only 8 out of 11 AI models gave the correct sequence (A>B>D>C) that aligns with engineering integrity. The three failing models consistently prioritized blaming the client over citing time constraints, exposing a systemic bias in responsibility attribution.
This seemingly simple logic puzzle exposed the real-world chain reasoning capability of current large models. Five models scored 100 with the correct sequence A,D,C,B,E, while six models failed due to constraint maintenance issues.
In the YZ Index v6 code execution test, the "SQL Monthly Retention Cohort" problem laid bare the true capabilities of 11 models. The result was brutal: 9 models scored 0, with only DeepSeek V4 Pro and Grok 4 managing a score of 66.7.
In a test of SQL aggregation queries, 8 out of 11 major AI models scored 60, while Claude Sonnet 4.6, Claude Opus 4.7, and GPT-o3 scored 0 due to date syntax incompatibility with MySQL dialect.
This week’s YZ Index v6 main leaderboard saw six legacy models removed and five new ones added simultaneously, reshuffling the top ten within a single week.
