提示词库 · 信息图 · 信息图 GPT Image 2 提示词:Leaked AI Benchmark Report Photo
信息图 GPT Image 2 提示词:Leaked AI Benchmark Report Photo
信息图

信息图 GPT Image 2 提示词:Leaked AI Benchmark Report Photo

Generates a realistic photograph of a computer screen displaying an academic technical report with bar charts and a detailed performance table.
场景
信息图
模型
GPT Image 2
语言
中文

📝 提示词

{ "type": "photograph of a computer monitor displaying an academic technical report", "style": "slightly angled screen photo, visible moire pattern, LCD pixel grid, slight glare, LaTeX document formatting, serif fonts", "document_header": { "left": "4 Benchmark Evaluation", "right": "{argument name="report title" default="DeepSeek-V4 Technical Report"}" }, "introductory_text": "Paragraph summarizing comprehensive evaluation of {argument name="main model name" default="DeepSeek-V4"} against {argument name="competitor model 1" default="GPT-5.3"}, {argument name="competitor model 2" default="Claude Opus 4.6"}, and {argument name="competitor model 3" default="Gemini 3.1 Pro Preview"}.", "visualizations": { "legend": "5 items with color codes: dark blue, grey, light grey, blue striped, light blue", "bar_charts": { "count": 6, "labels": [ "MMLU-Pro (EM)", "GPQA-Diamond (Pass@1)", "AIME 2025 (Pass@1)", "LiveCodeBench (Pass@1-COT)", "SWE-bench Verified (Resolved)", "Tau-bench (Average)" ] }, "caption": "Figure 1 | Performance comparison on core benchmarks. DeepSeek-V4 achieves state-of-the-art results across the majority of benchmarks." }, "data_table": { "columns": [ "Benchmark", "{argument name="main model name" default="DeepSeek-V4"}", "{argument name="competitor model 1" default="GPT-5.3"}", "{argument name="competitor model 2" default="Claude Opus 4.6"}", "{argument name="competitor model 3" default="Gemini 3.1 Pro Preview"}", "GPT-4.1" ], "categories": { "count": 4, "rows": [ {"label": "General", "icon": "globe/network", "sub_items": 3}, {"label": "Reasoning & Math", "icon": "calculator/clipboard", "sub_items": 3}, {"label": "Code", "icon": "code brackets", "sub_items": 3}, {"label": "Agent", "icon": "robot face", "sub_items": 3} ] } } }

🎯 适合场景

适合做图解、清单、路线图和知识长图:先锁定信息层级,再把文字量控制在模型能稳定处理的范围里。

💡 改写建议

  • 先替换变量里的品类、人物、城市、品牌色,不急着改整段结构。 把主体、构图和风格分开写,后续微调会更稳。
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