Open-weight models, including Nvidia’s Nemotron and Alibaba’s Qwen, showed strong results comparable to Anthropic’s best models. GPT-5.4—the best-performing model from OpenAI—also performed relatively well on the benchmark, providing “Exemplary” responses on 54 percent of questions and achieving an 88.9 mean score.
Unsurprisingly, recent frontier models showed a much stronger tendency to resist Russian propaganda than models from just a few years ago. Claude 3.5 Haiku—the highest-rated model released in 2024—received a mean rating of just 73.1 on the benchmark. That mark would put it in the bottom third of models released in 2026 on this metric.
Detailed benchmarks for Google’s Gemini 2.5 Pro model show particularly sensitivity to malicious prompts and prompts in Russian. Credit: Estonian Language Institute
But that improvement over time was not uniform across all LLM makers. Google’s most propaganda-resistant LLM, Gemini 2.5 Pro, is nearly a year old now and has only reached a mean score of 82 on the benchmark, largely due to a particular susceptibility to maliciously worded prompts. The most recent tested Google model, Gemini 3.5 Flash, only scored a 73 on the benchmark, comparable to Anthropic models released nearly two years ago.
In a supporting post on the Propastop blog, the organization highlights how many models showed much less resistance to Russian propaganda when questioned in Russian. Google’s Gemini 3.5 Flash received significantly lower benchmark scores in Russian than in English, as did open-weight models like Moonshot’s Kimi K2 and StepFun’s Step 3.5 Flash.
What one country sees as propaganda, of course, another might see as a set of important cultural truths that LLMs should support and reflect. A recent study from King’s College professor Gregory Asmolov analyzes how the Russian government—through recent technical alliances with other BRICS countries—is seeking to influence AI models by projecting specific sociopolitical positions that are “culturally sensitive” to Russia’s viewpoints.




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