{"id":20533,"date":"2024-09-26T09:31:43","date_gmt":"2024-09-26T01:31:43","guid":{"rendered":"https:\/\/www.1ai.net\/?p=20533"},"modified":"2024-09-26T10:42:05","modified_gmt":"2024-09-26T02:42:05","slug":"%e6%9d%8e%e9%a3%9e%e9%a3%9e%e5%88%9b%e4%b8%9a%e5%90%8e%e9%a6%96%e4%b8%aa%e4%b8%93%e8%ae%bf%ef%bc%9a%e8%a7%86%e8%a7%89%e7%a9%ba%e9%97%b4%e6%99%ba%e8%83%bd%e9%9d%9e%e5%b8%b8%e6%a0%b9%e6%9c%ac%ef%bc%8c","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/20533.html","title":{"rendered":"Google's Gemini 1.5 AI model evolves again: lower cost, better performance, faster responses"},"content":{"rendered":"<p>Technology media outlet The Decoder published a blog post on Sept. 24, reporting that<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e8%b0%b7%e6%ad%8c\" title=\"[View articles tagged with [Google]]\" target=\"_blank\" >Google<\/a>Under the Upgrade banner <a href=\"https:\/\/www.1ai.net\/en\/tag\/gemini\" title=\"[View articles tagged with [Gemini]]\" target=\"_blank\" >Gemini<\/a> 1.5 AI model, launched <strong>Gemini-1.5-Pro-002<\/strong>\u00a0and\u00a0<strong>Gemini-1.5-Flash-002<\/strong>It is less expensive, more powerful, and more responsive than previous versions.<\/p>\n<p><strong>Lower cost<\/strong><\/p>\n<p>Google lowered token input and output fees by up to 50% for Gemini-1.5-Pro-002 and Gemini-1.5-Flash-002, increased rate limits for both models, and reduced latency.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-20620\" title=\"b7a08ec4j00skec4x002md001hd00u1m\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/09\/b7a08ec4j00skec4x002md001hd00u1m.jpg\" alt=\"b7a08ec4j00skec4x002md001hd00u1m\" width=\"1921\" height=\"1081\" \/><\/p>\n<p>New pricing effective October 1, 2024<\/p>\n<p><strong>Better performance<\/strong><\/p>\n<p>Quoting from the press release, the performance of the new model is attached below:<\/p>\n<ul>\n<li>In the more challenging MMLU-Pro benchmark, the model's performance improved by about 7%.<\/li>\n<li>Math performance was significantly improved by 20% in the MATH and HiddenMath benchmarks.<\/li>\n<li>Visual and code-related tasks also improved, by 2-7% in the visual understanding and Python code generation assessments.<\/li>\n<\/ul>\n<p>Google claims that the models can now provide more helpful responses while maintaining content security standards. The company has improved the output style of the models based on feedback from developers, aiming for more accurate and cost-effective use.<\/p>\n<p><strong>Other improvements<\/strong><\/p>\n<p>Google has also upgraded its Gemini 1.5 experimental model, released in August, with the introduction of the\u00a0<strong>Gemini-1.5-Flash-8B-Exp-0924<\/strong>\u00a0Upgraded version with further enhancements to text and multimodal applications.<\/p>\n<p>Users can access the new Gemini models through Google AI Studio, the Gemini API, and Vertex AI (for Google Cloud customers). A chat-optimized version of Gemini 1.5 Pro-002 for Gemini Advanced users is coming soon.<\/p>","protected":false},"excerpt":{"rendered":"<p>Technology media The Decoder published a blog post on September 24th, reporting that Google has upgraded its Gemini 1.5 AI model, launching Gemini-1.5-Pro-002 and Gemini-1.5-Flash-002, which have lower cost, stronger performance and faster response than previous versions. Lower Cost Google has reduced token input and output fees by up to 50% for Gemini-1.5-Pro-002 and Gemini-1.5-Flash-002, increased rate limits for both models, and reduced latency. The new pricing is effective October 1, 2024. More Performance Quoting from the press release.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[436,281],"collection":[],"class_list":["post-20533","post","type-post","status-publish","format-standard","hentry","category-news","tag-gemini","tag-281"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/20533","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=20533"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/20533\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=20533"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=20533"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=20533"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=20533"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}