{"id":10867,"date":"2024-05-22T08:54:27","date_gmt":"2024-05-22T00:54:27","guid":{"rendered":"https:\/\/www.1ai.net\/?p=10867"},"modified":"2024-05-22T08:54:27","modified_gmt":"2024-05-22T00:54:27","slug":"%e7%99%be%e5%ba%a6%e5%ae%a3%e5%b8%83%e6%96%87%e5%bf%83%e5%a4%a7%e6%a8%a1%e5%9e%8b-enire-speed%e3%80%81enire-lite-%e5%85%a8%e9%9d%a2%e5%85%8d%e8%b4%b9%ef%bc%8c%e5%8d%b3%e5%88%bb%e7%94%9f%e6%95%88","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/10867.html","title":{"rendered":"Baidu announces that Wenxin Big Model ENIRE Speed and ENIRE Lite are now free, effective immediately"},"content":{"rendered":"<p data-vmark=\"3bba\">ByteDance released the Doubao large model last week and announced that the price of the large model has entered the &quot;centimeter era&quot;, claiming that it is &quot;99.3% cheaper than the industry&quot;. Alibaba Cloud also announced that Tongyi Qianwen Qwen-Long will reduce its price to 97% to respond.<\/p>\n<p data-vmark=\"8877\">Now,<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e7%99%be%e5%ba%a6\" title=\"[Sees articles containing [100 degrees] labels]\" target=\"_blank\" >Baidu<\/a><a href=\"https:\/\/www.1ai.net\/en\/tag\/%e6%96%87%e5%bf%83%e5%a4%a7%e6%a8%a1%e5%9e%8b\" title=\"[Sees articles with labels]\" target=\"_blank\" >Wenxin Large Model<\/a>Going a step further, it directly announced that its two main models, ENIRE Speed and ENIRE Lite, will be completely free, effective immediately.<\/p>\n<p data-vmark=\"aabb\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-10868\" title=\"7255dba2-b064-41cc-8445-959eebdb902d\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/05\/7255dba2-b064-41cc-8445-959eebdb902d.jpg\" alt=\"7255dba2-b064-41cc-8445-959eebdb902d\" width=\"1080\" height=\"415\" \/><\/p>\n<p data-vmark=\"072f\">These two large models were released in March this year and support 8K and 128k context lengths.<\/p>\n<p data-vmark=\"aae7\">According to Baidu&#039;s official introduction, ERNIE Speed is Baidu&#039;s latest self-developed high-performance large language model released in 2024. It has excellent general capabilities and is suitable as a base model for fine-tuning to better handle specific scenario problems. It also has excellent reasoning performance.<\/p>\n<p data-vmark=\"328d\">ERNIE Lite is a lightweight large language model developed by Baidu. It combines excellent model effects and reasoning performance, and is suitable for reasoning with low-computing AI accelerator cards.<\/p>","protected":false},"excerpt":{"rendered":"<p>Byte jumping last week released a large model of beanbag and announced that the price of large models into the \"ci era\", claiming that \"cheaper than the industry 99.3%\". Ali Cloud also announced that Tongyi thousand questions Qwen-Long price reduction of 97% to respond to the war. Now, Baidu Wenxin big model further, directly announced its two main models ENIRE Speed, ENIRE Lite free of charge, effective immediately. These two big models were released in March this year, supporting 8K and 128k context length. According to Baidu's official introduction, ENIRE Speed is Baidu's newest self-developed high-performance large language model released in 2024, with excellent generalization capabilities, suitable for fine-tuning as a base model to better handle specific scenarios, and with excellent<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[272,234],"collection":[],"class_list":["post-10867","post","type-post","status-publish","format-standard","hentry","category-news","tag-272","tag-234"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/10867","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=10867"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/10867\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=10867"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=10867"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=10867"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=10867"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}