The chat model evaluation encompasses both human subjective assessment and automated objective benchmarks. On the most representative human evaluation platform, LMSYS Chatbot Arena (which uses blind comparison), the Gemma 3 27B instruction-tuned model achieved an Elo score of 1338, ranking 9th among all models and surpassing several open-source models with far more parameters, including LLaMA 3 405B and Qwen2.5-70B, demonstrating its outstanding conversational interaction capability. On automated benchmarks, the model scored 67.5 on MMLU-Pro (measuring multidisciplinary understanding), 69.0 on MATH (mathematical reasoning), 29.7 on LiveCodeBench (code generation), 54.4 on Bird-SQL (SQL querying), 42.4 on GPQA Diamond (scientific reasoning), 74.9 on FACTS Grounding (factual accuracy), and 64.9 on MMMU (multimodal understanding), comprehensively showcasing its strong combined performance across knowledge, reasoning, code, and multimodal domains. Additionally, it achieved 75.1 on the global multilingual understanding test, reflecting excellent cross-lingual capability. In safety and responsibility evaluations, its memorization rate is as low as 0.001%, and no sensitive personal information was detected in privacy scans, meeting the requirements for responsible AI development.