The 2026-11-08 YZ Index Smoke quick test covered 13 models, with GPT-6 Astra taking the top spot for the day at 90.64 points. Smoke is a daily 10-question quick test suited to spotting short-term signals; it is not equivalent to the conclusions of the weekly Full leaderboard.
In today's Smoke evaluation, Doubao Pro's main leaderboard score fell from 87.60 to 79.57, driven by a sharp drop in the material constraint dimension from 84.30 to 58.50. The article examines whether this reflects question sampling volatility or a genuine regression.
In today's Smoke evaluation, GPT-5.5's Code Execution score rose from 69.50 to 99.80, while Material Constraints fell from 79.30 to 61.30; the main leaderboard score increased from 73.91 to 82.48.
The 2026-11-07 YZ Index Smoke quick test covered 14 models, with GPT-6 Astra ranking first for the day at 93.05. These small-sample daily results are best viewed as monitoring signals rather than long-term conclusions about model capability.
In today's Smoke evaluation, GPT-6.1 Sol's material constraint score fell 29.1 points to 60.70, while code execution rose 19.5 points to 94.50, leaving the main leaderboard score at 79.29. The opposing moves likely reflect small-sample question sampling rather than systematic model degradation.
In today's Smoke evaluation, GPT-6 Astra's material constraint score fell from 89.80 to 60.70, a drop of 29.1 points, while code execution rose from 75.00 to 94.50; its overall main leaderboard score declined from 81.66 to 79.29.
The 2026-11-06 YZ Index Smoke quick test covered 13 models, with Doubao Pro ranking first for the day at 87.6 points. Because the daily sample is small, the results are best viewed as short-term monitoring signals rather than long-term conclusions about model capability.
Deployed AI systems can behave very differently from their foundation models, so safety scores from system cards cannot be assumed to transfer. Teams should test complete deployment systems and account for measurement uncertainty.
Developers and deployers can now use two MLCommons benchmarks, AILuminate Safety 1.2.1 and AILuminate Jailbreak 1.1, to test AI systems' propensity to produce harmful content and how easily attackers can induce violations. Both benchmarks can be run on demand through MLCommons' new Candela service, and new public results for 27 systems have been released.
MLCommons has launched Candela, a benchmarking-as-a-service offering built on the AILuminate benchmarks to measure AI risk and reliability. It enables organizations to test complete AI systems across configurations and cite results for governance and procurement.
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The 2026-11-05 YZ Index Smoke quick test covered 13 models, with GPT-6 Astra and GPT-6.1 Sol tied for first at 81.66 points. The Smoke test is a daily 10-question quick test suited to short-term signals and is not equivalent to Full weekly leaderboard conclusions.
In the latest WDCD v3.1 round, Claude Opus 4.7 rose 8 points to 89.30 while Doubao Pro dropped 10.1 points, producing a pattern of three gains and five declines that sharply exposes differences in how stably models hold to constraints under multi-round pressure.
In WDCD v3.1, business rules are the hardest of the five major constraints to adhere to, with doubao-pro scoring only 1.2/4, while data boundaries show the widest differentiation and GPT-5.5 a 2.7-point cross-scenario gap.
