In Run #98 of the WDCD evaluation, 3 out of 11 models saw significant declines while only 1 improved, marking the most asymmetric cycle fluctuation since the pilot phase. Gemini 2.5 Pro and Qwen3 Max both dropped 7.5 points, GPT-5.5 fell 5.8 points, while 文心一言 4.5 bucked the trend with a +5 point gain.
The WDCD pilot data reveals that no model can fulfill commitments across all scenarios, and the "resource constraints" scenario—seemingly the simplest—tripped up every model, with champion grok-4 scoring just 2.17 out of 4.
The WDCD three-round decay test reveals a sobering reality for technical decision-makers: the R1 confirmation rate is 95%, the R2 resistance rate is 91%, but the R3 integrity rate plummets to 29%. Out of 330 R3 pressure tests, 209 ended in complete collapse (0 points), a breakdown rate of 63.3%. Models that confidently promise constraints in the first round betray them on the spot over 60% of the time when directly pressured in the third round.
In the latest WDCD (Winzheng Dynamic Contextual Decay) compliance test, 63.3% of large language models broke their own promises under three rounds of dialogue pressure.
As AI model capabilities converge, commitment ability—how reliably a model keeps its promises—is emerging as the next core indicator, reshaping enterprise selection and forcing vendors to prioritize compliance and controllability.
A rigorous test by Winzheng (winzheng.com) challenged 11 mainstream AI models with 30 carefully designed integrity tasks. The average honesty rate was just 60.4%, with the lowest dropping to 55%, raising serious concerns about AI reliability.
Many AI rankings are unreliable due to self-evaluation, fake code tests, single-run rankings, and sponsor influence. YZ Index from Winzheng disrupts this with rigorous methods like sandboxed execution, rolling averages, and zero-AI judging.
As a CTO or CIO, you may lose sleep over AI suppliers' promises. They verbally guarantee data isolation, but leak user privacy under pressure? This is not sci-fi but a real risk. The WDCD Guardrail Test cuts to the chase, simulating high-pressure scenarios to check if models break promises. Stop blindly trusting hype—see the real scores and avoid data disasters.
By utilizing the weekly updated YZ Index open data from Winzheng (winzheng.com), developers can make data-driven decisions to compare model performance, avoid pitfalls, and save up to 20% in R&D costs. This professional AI model evaluation index covers hundreds of popular models across dimensions like performance, efficiency, cost, and stability.
Winzheng (winzheng.com) has upgraded its homepage from a simple product showcase into an AI intelligence terminal, featuring a Bloomberg-style real-time dashboard, AI-powered smart search, curated headline news feeds, a data trust wall, and embedded widgets for sharing YZ Index rankings. The redesign aims to deliver trusted, real-time, data-driven insights, helping users stay ahead in the fast-evolving AI landscape.
This article compares Claude Opus 4.7 and GPT-5.5 using the YZ Index AI model comparison tool from Winzheng, providing data-driven insights across five dimensions with radar charts, bar charts, API pricing, and scenario recommendations.
This week, Grok 3 shockingly tops the YZ Index with a score of 86.88, edging out Doubao Pro by just 0.44 points. Dive into the analysis of which models are surging and which are slipping.
The YZ Index WDCD Commitment Test, launched by Winzheng (winzheng.com), uses a 3-round, 30-question design to precisely dissect AI’s “credibility crisis.” It exposes the hidden danger of AI failing to honor its promises, urging enterprises to move beyond flashy benchmark scores and focus on true reliability.
The first round of WDCD testing by YZ Index reveals Qwen3-Max leading with 66.67 points, while many major models quickly collapse under stress. The average score is only 60.53, highlighting widespread compliance flaws in current AI systems.
In this week's evaluation, Claude Sonnet 4.6 experienced a significant drop from a full score to zero in a task named "SQL: Suspected Duplicate Payment Identification," drawing widespread attention to its execution dimension. Through detailed analysis of the original task and the model's response, we can better understand the root cause of this scoring change.
DeepSeek V3 exhibited a contradictory performance in this week's evaluation: significant improvements in multiple capability metrics, with the overall score rising from 52.9 to 66.6, but a cliff-like drop in the stability dimension. This phenomenon of "enhanced capabilities but unstable output" deserves in-depth analysis.
In this week's Winzheng AI evaluation, Doubao Pro's overall score increased by 16.1 points, but its stability dimension dropped sharply by 19.8 points to 34.7, revealing severe challenges in maintaining answer consistency. This phenomenon may result from technical adjustments like temperature parameter changes or model routing updates, reflecting a trade-off between capability enhancement and output predictability.
This week's YZ Index evaluation captures a rare synchronous improvement in the "task expression" dimension across 10 out of 11 mainstream AI models, while Claude Opus 4.6 uniquely breaks through in the "material constraint" dimension. The report analyzes these developments and offers developer selection advice for different application scenarios.
YZ Index testing reveals GPT-4o's code execution (v5) version suffers major performance crisis, with scores dropping from 78.0 to 62.8 out of 100. Six out of seven evaluation dimensions show dramatic declines, raising serious concerns about model stability and reliability.
GPT-4o suffered a dramatic 10.3-point drop in Material Constraints this week, falling to last place among 11 models, while Baidu's Wenxin 4.0 became the only model to achieve positive growth in core dimensions.
