[{"data":1,"prerenderedAt":1197},["ShallowReactive",2],{"header-counts":3,"footer-counts":6,"model-gemini-2.5-pro":9},{"tools":4,"reviews":5},65,7,{"tools":4,"reviews":5,"playbooks":7,"news":8},10,8,{"id":10,"title":11,"apiCompatible":12,"benchmarks":14,"body":27,"category":1163,"contextWindow":1164,"description":1165,"extension":1166,"maxOutput":1167,"meta":1168,"navigation":206,"path":1169,"pricing":1170,"published":1171,"relatedTools":1172,"releaseDate":1175,"seo":1176,"slug":1177,"stem":1178,"strengths":1179,"updated":1171,"useCases":1185,"vendor":1190,"vendorEn":1190,"weaknesses":1191,"__hash__":1196},"models\u002Fmodels\u002Fgemini-2.5-pro.md","Gemini 2.5 Pro",[13],"google",[15,18,21,24],{"name":16,"score":17},"SWE-bench Verified","63.8%",{"name":19,"score":20},"HumanEval","92.1%",{"name":22,"score":23},"MMLU","87.1%",{"name":25,"score":26},"GPQA Diamond","56.4%",{"type":28,"value":29,"toc":1143},"minimark",[30,34,38,41,46,49,65,79,82,85,172,176,183,312,318,322,329,340,343,347,351,486,490,650,657,660,753,756,832,846,849,852,906,909,912,915,930,933,1038,1044,1055,1058,1110,1113,1139],[31,32,33],"h2",{"id":33},"概述",[35,36,37],"p",{},"Gemini 2.5 Pro 是 Google 于 2025 年 3 月发布的旗舰模型，最大亮点是 100 万 token 的上下文窗口——全网最长。可以一次性处理整本书、整个代码仓库或数小时的视频。",[31,39,40],{"id":40},"核心能力",[42,43,45],"h3",{"id":44},"_100-万-token-上下文","100 万 token 上下文",[35,47,48],{},"这是 Gemini 2.5 Pro 的杀手锏。100 万 token 约等于：",[50,51,52,56,59,62],"ul",{},[53,54,55],"li",{},"一本 75 万字的中文小说",[53,57,58],{},"一个 10 万行代码的中型项目",[53,60,61],{},"10 小时 1080p 视频",[53,63,64],{},"一次完整的学术会议所有论文",[35,66,67,68,73,74,78],{},"但要注意\"中间遗忘\"——超过 500K 后召回率明显下降，详见 ",[69,70,72],"a",{"href":71},"\u002Fwiki\u002Fcontext-engineering.html","Context Engineering","。Google 自己的 Needle-in-Haystack 测试虽然全 100% 命中，但",[75,76,77],"strong",{},"真实业务中的多 hop 推理","在长上下文下仍然不稳。",[42,80,81],{"id":81},"多模态",[35,83,84],{},"原生支持图片、视频、音频输入。视频理解能力是所有大模型中最强的——可以精确识别视频中的动作、物体、场景、对话内容。",[86,87,92],"pre",{"className":88,"code":89,"language":90,"meta":91,"style":91},"language-python shiki shiki-themes github-light github-dark","# 视频输入\ncontent_part = {\n    \"file_data\": {\n        \"mime_type\": \"video\u002Fmp4\",\n        \"file_uri\": \"gs:\u002F\u002Fbucket\u002Flecture.mp4\",\n    }\n}\n# 1 小时视频约消耗 100K-200K token\n","python","",[93,94,95,104,118,128,143,156,162,167],"code",{"__ignoreMap":91},[96,97,100],"span",{"class":98,"line":99},"line",1,[96,101,103],{"class":102},"sJ8bj","# 视频输入\n",[96,105,107,111,115],{"class":98,"line":106},2,[96,108,110],{"class":109},"sVt8B","content_part ",[96,112,114],{"class":113},"szBVR","=",[96,116,117],{"class":109}," {\n",[96,119,121,125],{"class":98,"line":120},3,[96,122,124],{"class":123},"sZZnC","    \"file_data\"",[96,126,127],{"class":109},": {\n",[96,129,131,134,137,140],{"class":98,"line":130},4,[96,132,133],{"class":123},"        \"mime_type\"",[96,135,136],{"class":109},": ",[96,138,139],{"class":123},"\"video\u002Fmp4\"",[96,141,142],{"class":109},",\n",[96,144,146,149,151,154],{"class":98,"line":145},5,[96,147,148],{"class":123},"        \"file_uri\"",[96,150,136],{"class":109},[96,152,153],{"class":123},"\"gs:\u002F\u002Fbucket\u002Flecture.mp4\"",[96,155,142],{"class":109},[96,157,159],{"class":98,"line":158},6,[96,160,161],{"class":109},"    }\n",[96,163,164],{"class":98,"line":5},[96,165,166],{"class":109},"}\n",[96,168,169],{"class":98,"line":8},[96,170,171],{"class":102},"# 1 小时视频约消耗 100K-200K token\n",[42,173,175],{"id":174},"thinking-模式自适应推理","Thinking 模式（自适应推理）",[35,177,178,179,182],{},"Gemini 2.5 系列内置 ",[75,180,181],{},"dynamic thinking","——模型自动决定是否要\"想一想\"。也可以手动控制：",[86,184,186],{"className":88,"code":185,"language":90,"meta":91,"style":91},"from google import genai\n\nclient = genai.Client(api_key=\"...\")\n\nresp = client.models.generate_content(\n    model=\"gemini-2.5-pro\",\n    contents=\"证明费马小定理\",\n    config={\n        \"thinking_config\": {\"thinking_budget\": 8000},  # 0 = 关闭\n    },\n)\n",[93,187,188,202,208,230,234,244,256,268,278,302,307],{"__ignoreMap":91},[96,189,190,193,196,199],{"class":98,"line":99},[96,191,192],{"class":113},"from",[96,194,195],{"class":109}," google ",[96,197,198],{"class":113},"import",[96,200,201],{"class":109}," genai\n",[96,203,204],{"class":98,"line":106},[96,205,207],{"emptyLinePlaceholder":206},true,"\n",[96,209,210,213,215,218,222,224,227],{"class":98,"line":120},[96,211,212],{"class":109},"client ",[96,214,114],{"class":113},[96,216,217],{"class":109}," genai.Client(",[96,219,221],{"class":220},"s4XuR","api_key",[96,223,114],{"class":113},[96,225,226],{"class":123},"\"...\"",[96,228,229],{"class":109},")\n",[96,231,232],{"class":98,"line":130},[96,233,207],{"emptyLinePlaceholder":206},[96,235,236,239,241],{"class":98,"line":145},[96,237,238],{"class":109},"resp ",[96,240,114],{"class":113},[96,242,243],{"class":109}," client.models.generate_content(\n",[96,245,246,249,251,254],{"class":98,"line":158},[96,247,248],{"class":220},"    model",[96,250,114],{"class":113},[96,252,253],{"class":123},"\"gemini-2.5-pro\"",[96,255,142],{"class":109},[96,257,258,261,263,266],{"class":98,"line":5},[96,259,260],{"class":220},"    contents",[96,262,114],{"class":113},[96,264,265],{"class":123},"\"证明费马小定理\"",[96,267,142],{"class":109},[96,269,270,273,275],{"class":98,"line":8},[96,271,272],{"class":220},"    config",[96,274,114],{"class":113},[96,276,277],{"class":109},"{\n",[96,279,281,284,287,290,292,296,299],{"class":98,"line":280},9,[96,282,283],{"class":123},"        \"thinking_config\"",[96,285,286],{"class":109},": {",[96,288,289],{"class":123},"\"thinking_budget\"",[96,291,136],{"class":109},[96,293,295],{"class":294},"sj4cs","8000",[96,297,298],{"class":109},"},  ",[96,300,301],{"class":102},"# 0 = 关闭\n",[96,303,304],{"class":98,"line":7},[96,305,306],{"class":109},"    },\n",[96,308,310],{"class":98,"line":309},11,[96,311,229],{"class":109},[35,313,314,317],{},[93,315,316],{},"thinking_budget=0"," 禁用推理（变成快速模式），数值越大推理越深。",[42,319,321],{"id":320},"flash-版本","Flash 版本",[35,323,324,328],{},[69,325,327],{"href":326},"\u002Fmodels\u002Fgemini-2.5-flash.html","Gemini 2.5 Flash"," 是 Pro 的轻量版：",[50,330,331,334,337],{},[53,332,333],{},"速度：Pro 的 5-10 倍",[53,335,336],{},"价格：Input $0.075\u002FM（Pro 的 6%）",[53,338,339],{},"能力：保留 Pro 约 85% 的能力",[35,341,342],{},"对于高吞吐场景（客服 bot、批量分类、内容审核），Flash 的性价比无敌。",[31,344,346],{"id":345},"api-调用示例","API 调用示例",[42,348,350],{"id":349},"python-sdk新版-google-genai","Python SDK（新版 google-genai）",[86,352,354],{"className":88,"code":353,"language":90,"meta":91,"style":91},"from google import genai\n\nclient = genai.Client(api_key=\"AIza...\")\n\nresp = client.models.generate_content(\n    model=\"gemini-2.5-pro\",\n    contents=\"Hello, summarize this PDF.\",\n    config={\n        \"temperature\": 1.0,\n        \"max_output_tokens\": 8000,\n        \"response_mime_type\": \"application\u002Fjson\",   # 强制 JSON 输出\n    },\n)\nprint(resp.text)\n",[93,355,356,366,370,387,391,399,409,420,428,440,451,467,472,477],{"__ignoreMap":91},[96,357,358,360,362,364],{"class":98,"line":99},[96,359,192],{"class":113},[96,361,195],{"class":109},[96,363,198],{"class":113},[96,365,201],{"class":109},[96,367,368],{"class":98,"line":106},[96,369,207],{"emptyLinePlaceholder":206},[96,371,372,374,376,378,380,382,385],{"class":98,"line":120},[96,373,212],{"class":109},[96,375,114],{"class":113},[96,377,217],{"class":109},[96,379,221],{"class":220},[96,381,114],{"class":113},[96,383,384],{"class":123},"\"AIza...\"",[96,386,229],{"class":109},[96,388,389],{"class":98,"line":130},[96,390,207],{"emptyLinePlaceholder":206},[96,392,393,395,397],{"class":98,"line":145},[96,394,238],{"class":109},[96,396,114],{"class":113},[96,398,243],{"class":109},[96,400,401,403,405,407],{"class":98,"line":158},[96,402,248],{"class":220},[96,404,114],{"class":113},[96,406,253],{"class":123},[96,408,142],{"class":109},[96,410,411,413,415,418],{"class":98,"line":5},[96,412,260],{"class":220},[96,414,114],{"class":113},[96,416,417],{"class":123},"\"Hello, summarize this PDF.\"",[96,419,142],{"class":109},[96,421,422,424,426],{"class":98,"line":8},[96,423,272],{"class":220},[96,425,114],{"class":113},[96,427,277],{"class":109},[96,429,430,433,435,438],{"class":98,"line":280},[96,431,432],{"class":123},"        \"temperature\"",[96,434,136],{"class":109},[96,436,437],{"class":294},"1.0",[96,439,142],{"class":109},[96,441,442,445,447,449],{"class":98,"line":7},[96,443,444],{"class":123},"        \"max_output_tokens\"",[96,446,136],{"class":109},[96,448,295],{"class":294},[96,450,142],{"class":109},[96,452,453,456,458,461,464],{"class":98,"line":309},[96,454,455],{"class":123},"        \"response_mime_type\"",[96,457,136],{"class":109},[96,459,460],{"class":123},"\"application\u002Fjson\"",[96,462,463],{"class":109},",   ",[96,465,466],{"class":102},"# 强制 JSON 输出\n",[96,468,470],{"class":98,"line":469},12,[96,471,306],{"class":109},[96,473,475],{"class":98,"line":474},13,[96,476,229],{"class":109},[96,478,480,483],{"class":98,"line":479},14,[96,481,482],{"class":294},"print",[96,484,485],{"class":109},"(resp.text)\n",[42,487,489],{"id":488},"context-caching显式-api与-openai-自动-cache-不同","Context Caching（显式 API，与 OpenAI 自动 cache 不同）",[86,491,493],{"className":88,"code":492,"language":90,"meta":91,"style":91},"# 1. 创建 cache\ncache = client.caches.create(\n    model=\"gemini-2.5-pro\",\n    config={\n        \"contents\": [{\"role\": \"user\", \"parts\": [{\"text\": LONG_DOCUMENT}]}],\n        \"ttl\": \"3600s\",   # 1 小时\n    },\n)\n\n# 2. 用 cache 名引用\nresp = client.models.generate_content(\n    model=\"gemini-2.5-pro\",\n    contents=\"What are the key findings?\",\n    config={\"cached_content\": cache.name},\n)\n# Input 价格 -75%，再加按小时存储费\n",[93,494,495,500,510,520,528,563,578,582,586,590,595,603,613,624,639,644],{"__ignoreMap":91},[96,496,497],{"class":98,"line":99},[96,498,499],{"class":102},"# 1. 创建 cache\n",[96,501,502,505,507],{"class":98,"line":106},[96,503,504],{"class":109},"cache ",[96,506,114],{"class":113},[96,508,509],{"class":109}," client.caches.create(\n",[96,511,512,514,516,518],{"class":98,"line":120},[96,513,248],{"class":220},[96,515,114],{"class":113},[96,517,253],{"class":123},[96,519,142],{"class":109},[96,521,522,524,526],{"class":98,"line":130},[96,523,272],{"class":220},[96,525,114],{"class":113},[96,527,277],{"class":109},[96,529,530,533,536,539,541,544,547,550,552,555,557,560],{"class":98,"line":145},[96,531,532],{"class":123},"        \"contents\"",[96,534,535],{"class":109},": [{",[96,537,538],{"class":123},"\"role\"",[96,540,136],{"class":109},[96,542,543],{"class":123},"\"user\"",[96,545,546],{"class":109},", ",[96,548,549],{"class":123},"\"parts\"",[96,551,535],{"class":109},[96,553,554],{"class":123},"\"text\"",[96,556,136],{"class":109},[96,558,559],{"class":294},"LONG_DOCUMENT",[96,561,562],{"class":109},"}]}],\n",[96,564,565,568,570,573,575],{"class":98,"line":158},[96,566,567],{"class":123},"        \"ttl\"",[96,569,136],{"class":109},[96,571,572],{"class":123},"\"3600s\"",[96,574,463],{"class":109},[96,576,577],{"class":102},"# 1 小时\n",[96,579,580],{"class":98,"line":5},[96,581,306],{"class":109},[96,583,584],{"class":98,"line":8},[96,585,229],{"class":109},[96,587,588],{"class":98,"line":280},[96,589,207],{"emptyLinePlaceholder":206},[96,591,592],{"class":98,"line":7},[96,593,594],{"class":102},"# 2. 用 cache 名引用\n",[96,596,597,599,601],{"class":98,"line":309},[96,598,238],{"class":109},[96,600,114],{"class":113},[96,602,243],{"class":109},[96,604,605,607,609,611],{"class":98,"line":469},[96,606,248],{"class":220},[96,608,114],{"class":113},[96,610,253],{"class":123},[96,612,142],{"class":109},[96,614,615,617,619,622],{"class":98,"line":474},[96,616,260],{"class":220},[96,618,114],{"class":113},[96,620,621],{"class":123},"\"What are the key findings?\"",[96,623,142],{"class":109},[96,625,626,628,630,633,636],{"class":98,"line":479},[96,627,272],{"class":220},[96,629,114],{"class":113},[96,631,632],{"class":109},"{",[96,634,635],{"class":123},"\"cached_content\"",[96,637,638],{"class":109},": cache.name},\n",[96,640,642],{"class":98,"line":641},15,[96,643,229],{"class":109},[96,645,647],{"class":98,"line":646},16,[96,648,649],{"class":102},"# Input 价格 -75%，再加按小时存储费\n",[35,651,652,653,656],{},"显式 cache 适合",[75,654,655],{},"少量超长文档反复问","的场景（合同、财报）。注意 cache 不是免费——按存储时长计费 $4.50\u002FM-token\u002Fhour。",[31,658,659],{"id":659},"关键参数",[661,662,663,679],"table",{},[664,665,666],"thead",{},[667,668,669,673,676],"tr",{},[670,671,672],"th",{},"参数",[670,674,675],{},"推荐",[670,677,678],{},"说明",[680,681,682,696,709,722,735],"tbody",{},[667,683,684,690,693],{},[685,686,687],"td",{},[93,688,689],{},"temperature",[685,691,692],{},"1.0（默认）",[685,694,695],{},"推理模型，不要改",[667,697,698,703,706],{},[685,699,700],{},[93,701,702],{},"top_p",[685,704,705],{},"0.95（默认）",[685,707,708],{},"Gemini 默认就开了 nucleus sampling",[667,710,711,716,719],{},[685,712,713],{},[93,714,715],{},"max_output_tokens",[685,717,718],{},"显式设",[685,720,721],{},"否则默认 8192，长输出会截断",[667,723,724,729,732],{},[685,725,726],{},[93,727,728],{},"thinking_budget",[685,730,731],{},"0 \u002F 8000 \u002F 32000",[685,733,734],{},"简单任务 0，复杂推理拉满",[667,736,737,742,747],{},[685,738,739],{},[93,740,741],{},"response_mime_type",[685,743,744],{},[93,745,746],{},"application\u002Fjson",[685,748,749,750],{},"强制 JSON，配合 ",[93,751,752],{},"response_schema",[31,754,755],{"id":755},"定价",[661,757,758,774],{},[664,759,760],{},[667,761,762,765,768,771],{},[670,763,764],{},"项目",[670,766,767],{},"Pro（≤200K input）",[670,769,770],{},"Pro（>200K input）",[670,772,773],{},"Flash",[680,775,776,790,804,818],{},[667,777,778,781,784,787],{},[685,779,780],{},"Input",[685,782,783],{},"$1.25\u002FM",[685,785,786],{},"$2.50\u002FM",[685,788,789],{},"$0.075\u002FM",[667,791,792,795,798,801],{},[685,793,794],{},"Output",[685,796,797],{},"$10\u002FM",[685,799,800],{},"$15\u002FM",[685,802,803],{},"$0.30\u002FM",[667,805,806,809,812,815],{},[685,807,808],{},"Cached Input",[685,810,811],{},"$0.31\u002FM",[685,813,814],{},"$0.625\u002FM",[685,816,817],{},"$0.01875\u002FM",[667,819,820,823,826,829],{},[685,821,822],{},"Cache 存储",[685,824,825],{},"$4.50\u002FM\u002Fhour",[685,827,828],{},"—",[685,830,831],{},"$1.00\u002FM\u002Fhour",[35,833,834,837,838,841,842,845],{},[75,835,836],{},"重要","：Pro 的价格在 200K input 处",[75,839,840],{},"翻倍","！很多人没注意到这点。如果你的 prompt 长期超过 200K，",[75,843,844],{},"先做检索压缩再喂给模型","比硬塞 600K 划算。",[31,847,848],{"id":848},"视频理解的真实场景",[35,850,851],{},"Gemini Pro 在视频上的护城河目前没人能赶上：",[661,853,854,864],{},[664,855,856],{},[667,857,858,861],{},[670,859,860],{},"任务",[670,862,863],{},"价值",[680,865,866,874,882,890,898],{},[667,867,868,871],{},[685,869,870],{},"安防录像分析",[685,872,873],{},"找特定行为发生时刻",[667,875,876,879],{},[685,877,878],{},"在线课程切片",[685,880,881],{},"自动出章节标题 \u002F 摘要 \u002F 字幕",[667,883,884,887],{},[685,885,886],{},"电商商品视频",[685,888,889],{},"自动出产品标签 \u002F 文案",[667,891,892,895],{},[685,893,894],{},"会议录像",[685,896,897],{},"自动出会议纪要 \u002F TODO",[667,899,900,903],{},[685,901,902],{},"故障复盘",[685,904,905],{},"看操作录屏定位用户卡点",[35,907,908],{},"调用价：1 分钟 1080p 视频约 250-500 input token，1 小时视频 ~30K token，远比想象中便宜。",[31,910,911],{"id":911},"国内使用",[35,913,914],{},"Google API 不对中国大陆开放，需要：",[916,917,918,921,924,927],"ol",{},[53,919,920],{},"海外网络环境 + Google AI Studio API",[53,922,923],{},"Google Cloud Vertex AI（企业级，要海外 GCP 账号）",[53,925,926],{},"通过 OpenRouter \u002F 其他中转平台",[53,928,929],{},"AWS Bedrock 暂不支持 Gemini（只有 Anthropic \u002F Llama）",[31,931,932],{"id":932},"与其他模型怎么选",[661,934,935,950],{},[664,936,937],{},[667,938,939,942,944,947],{},[670,940,941],{},"维度",[670,943,11],{},[670,945,946],{},"Claude Sonnet 4",[670,948,949],{},"GPT-5",[680,951,952,966,979,991,1002,1015,1026],{},[667,953,954,957,960,963],{},[685,955,956],{},"上下文",[685,958,959],{},"1M（全网最长）",[685,961,962],{},"200K",[685,964,965],{},"400K",[667,967,968,971,974,977],{},[685,969,970],{},"编程",[685,972,973],{},"★★★★☆",[685,975,976],{},"★★★★★",[685,978,973],{},[667,980,981,983,986,989],{},[685,982,81],{},[685,984,985],{},"★★★★★（含视频）",[685,987,988],{},"★★★☆☆（仅图片）",[685,990,973],{},[667,992,993,996,998,1000],{},[685,994,995],{},"推理",[685,997,973],{},[685,999,973],{},[685,1001,976],{},[667,1003,1004,1007,1010,1013],{},[685,1005,1006],{},"价格",[685,1008,1009],{},"$1.25\u002F$10",[685,1011,1012],{},"$3\u002F$15",[685,1014,1009],{},[667,1016,1017,1020,1022,1024],{},[685,1018,1019],{},"工具调用稳定性",[685,1021,973],{},[685,1023,976],{},[685,1025,976],{},[667,1027,1028,1031,1034,1036],{},[685,1029,1030],{},"国内可用",[685,1032,1033],{},"❌",[685,1035,1033],{},[685,1037,1033],{},[35,1039,1040,1043],{},[75,1041,1042],{},"建议","：",[50,1045,1046,1049,1052],{},[53,1047,1048],{},"需要处理超长内容或视频 → Gemini 2.5 Pro",[53,1050,1051],{},"主力编程 → Claude Sonnet 4",[53,1053,1054],{},"推理 \u002F Agent → GPT-5 或 Sonnet 4",[31,1056,1057],{"id":1057},"避坑清单",[50,1059,1060,1066,1074,1082,1094,1100],{},[53,1061,1062,1065],{},[75,1063,1064],{},"200K 价格断点","：超过就翻倍。Prompt 设计时尽量切在 200K 以内。",[53,1067,1068,1073],{},[75,1069,1070,1072],{},[93,1071,728],{}," 默认开","：意味着即使简单任务也可能多花 token。批量场景显式设 0。",[53,1075,1076,1081],{},[75,1077,1078,1080],{},[93,1079,715],{}," 不设会截断","：默认 8192，长输出务必显式调高到 65536。",[53,1083,1084,1090,1091,1093],{},[75,1085,1086,1089],{},[93,1087,1088],{},"response_mime_type=application\u002Fjson"," 不够","：还要配 ",[93,1092,752],{}," 才是强约束，否则模型可能输出\"\u002F\u002F 注释\"破坏 JSON。",[53,1095,1096,1099],{},[75,1097,1098],{},"国内中转质量参差","：OpenRouter 是相对稳定的选择；自建中转要注意 Google 的速率限制。",[53,1101,1102,1105,1106,1109],{},[75,1103,1104],{},"Cache 存储费","：不用了记得 ",[93,1107,1108],{},"caches.delete()","，否则按小时持续扣费。",[31,1111,1112],{"id":1112},"延伸阅读",[50,1114,1115,1120,1125,1132],{},[53,1116,1117,1118],{},"轻量版本：",[69,1119,327],{"href":326},[53,1121,1122,1123],{},"上下文管理：",[69,1124,72],{"href":71},[53,1126,1127,1128],{},"多模态基础：",[69,1129,1131],{"href":1130},"\u002Fwiki\u002Fembedding.html","Embedding",[53,1133,1134,1135],{},"工具调用：",[69,1136,1138],{"href":1137},"\u002Fwiki\u002Ffunction-calling.html","Function Calling",[1140,1141,1142],"style",{},"html pre.shiki code .sJ8bj, html code.shiki .sJ8bj{--shiki-default:#6A737D;--shiki-dark:#6A737D}html pre.shiki code .sVt8B, html code.shiki .sVt8B{--shiki-default:#24292E;--shiki-dark:#E1E4E8}html pre.shiki code .szBVR, html code.shiki .szBVR{--shiki-default:#D73A49;--shiki-dark:#F97583}html pre.shiki code .sZZnC, html code.shiki .sZZnC{--shiki-default:#032F62;--shiki-dark:#9ECBFF}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html pre.shiki code .s4XuR, html code.shiki .s4XuR{--shiki-default:#E36209;--shiki-dark:#FFAB70}html pre.shiki code .sj4cs, html code.shiki .sj4cs{--shiki-default:#005CC5;--shiki-dark:#79B8FF}",{"title":91,"searchDepth":120,"depth":120,"links":1144},[1145,1146,1152,1156,1157,1158,1159,1160,1161,1162],{"id":33,"depth":106,"text":33},{"id":40,"depth":106,"text":40,"children":1147},[1148,1149,1150,1151],{"id":44,"depth":120,"text":45},{"id":81,"depth":120,"text":81},{"id":174,"depth":120,"text":175},{"id":320,"depth":120,"text":321},{"id":345,"depth":106,"text":346,"children":1153},[1154,1155],{"id":349,"depth":120,"text":350},{"id":488,"depth":120,"text":489},{"id":659,"depth":106,"text":659},{"id":755,"depth":106,"text":755},{"id":848,"depth":106,"text":848},{"id":911,"depth":106,"text":911},{"id":932,"depth":106,"text":932},{"id":1057,"depth":106,"text":1057},{"id":1112,"depth":106,"text":1112},"multimodal",1000000,"Google Gemini 2.5 Pro 旗舰多模态模型，100 万 token 业界最长上下文，图像 \u002F 音频 \u002F 视频 \u002F 代码原生混合推理，Vertex AI 企业级 SLA 集成，Flash 版本提供 1\u002F16 价格兜底。","md",65536,{},"\u002Fmodels\u002Fgemini-2.5-pro","Input $1.25\u002FM · Output $10\u002FM · 闪存 $0.075\u002FM","2026-06-21",[1173,1174],"coding\u002Fide\u002Fcursor","coding\u002Fapi\u002Fopenrouter","2025-03-25",{"title":11,"description":1165},"gemini-2.5-pro","models\u002Fgemini-2.5-pro",[1180,1181,1182,1183,1184],"100 万 token 上下文，全网最长，可处理整本书\u002F整个代码仓库","多模态原生支持（图片\u002F视频\u002F音频\u002F代码）","Flash 版本极快极便宜，适合高吞吐场景","Google 生态集成（Vertex AI \u002F AI Studio）","视频理解能力业界最强",[1186,1187,1188,1189],"超长文档\u002F书籍\u002F代码仓库分析","视频内容理解与总结","多模态应用开发","高吞吐低成本场景（Flash 版本）","Google",[1192,1193,1194,1195],"国内无法直连，需要海外网络","编程实操中不如 Claude Sonnet 4 稳定","API 文档和生态不如 OpenAI\u002FAnthropic 完善","长上下文下有'中间遗忘'现象","eZd7lsemIRUzU2r9EjLKYC-zLT_6T1UqdVcIji-PGbw",1782316489331]