{"id":112109,"date":"2026-07-20T15:53:08","date_gmt":"2026-07-20T15:53:08","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/112109\/"},"modified":"2026-07-20T15:53:08","modified_gmt":"2026-07-20T15:53:08","slug":"google-plans-new-chip-to-speed-up-gemini-model-inference-ukraine-news","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/112109\/","title":{"rendered":"Google plans new chip to speed up Gemini model inference | Ukraine news"},"content":{"rendered":"<p style=\"font-style:italic;font-weight:500;font-size:18px;line-height:1.5\">Google\u2019s upcoming custom chip could transform Gemini performance across cloud and devices. Technical specifics remain secret, but industry expectations are high.<\/p>\n<p>Google plans to release a new chip designed to run Gemini models more efficiently. Such hardware solution is intended to boost artificial intelligence performance in the cloud and on devices where Gemini is used. Details of architecture and specifications are currently not disclosed, however industry expectations are that the new chip will improve neural network processing speed and reduce energy consumption during use of Gemini.<\/p>\n<p>Expected chip benefits<\/p>\n<p>Among the possible benefits are:<\/p>\n<p>increased energy efficiency when working with large Gemini models;<br \/>\nimproved throughput and reduced latency in responses;<br \/>\nan optimized instruction set for tensor operations and faster inference;<br \/>\nbetter integration with Google Cloud services and Gemini-based devices.<\/p>\n<p>Potential market and service impact<\/p>\n<p>The launch of the new chip could lower overall costs of using large models and accelerate the deployment of AI solutions in business and in provider services. Such steps demonstrate Google\u2019s aim to develop its own hardware platform to support the growing needs of the Gemini model in computational power.<\/p>\n","protected":false},"excerpt":{"rendered":"Google\u2019s upcoming custom chip could transform Gemini performance across cloud and devices. Technical specifics remain secret, but industry&hellip;\n","protected":false},"author":2,"featured_media":112110,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[57547,57548,2408,57549,132,57550,1430,57551,57546,66],"class_list":["post-112109","post","type-post","status-publish","format-standard","has-post-thumbnail","category-google","tag-ai-inference-chip","tag-energy-efficient-ai-chip","tag-gemini","tag-gemini-inference-accelerator","tag-google","tag-google-cloud-hardware","tag-google-gemini","tag-google-gemini-chip","tag-google-gemini-chip-gemini-inference-accelerator-ai-inference-chip-google-cloud-hardware-energy-efficient-ai-chip","tag-news"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/112109","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=112109"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/112109\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/112110"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=112109"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=112109"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=112109"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}