{"id":688786,"date":"2026-05-23T04:43:26","date_gmt":"2026-05-23T04:43:26","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/688786\/"},"modified":"2026-05-23T04:43:26","modified_gmt":"2026-05-23T04:43:26","slug":"google-says-these-are-the-best-ai-models-for-android-app-coding","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/688786\/","title":{"rendered":"Google says these are the best AI models for Android app coding"},"content":{"rendered":"

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Google has once again updated its \u201cAndroid Bench\u201d rankings for the best AI models for Android app development, with a bunch of new \u201copen-weight\u201d models as well as more details on the tokens used and cost of using these models.<\/p>\n

One thing that large language models have gotten really good at is coding, with their ability to aid in the development of apps and other software projects also leading to the rise of \u201cvibe coding.\u201d Earlier this year, Google published a new benchmark ranking that showcased the \u201cbest\u201d AI models for Android app development, taking into account common Android development tasks as well as how these models handle best practices. <\/p>\n

When the \u201cAndroid Bench\u201d first debuted<\/a>, Gemini 3.1 Pro led the pack, and OpenAI\u2019s GPT 5.4 later tied<\/a> for the top slot. <\/p>\n

As of the May 18, 2026 update<\/a>, there\u2019s a new king in town. According to Google, GPT 5.5 is currently the best AI model for Android app development, beating out GPT 5.4 and Gemini 3.1 Pro by a little under 2%.<\/p>\n

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But this latest update also puts things into perspective much better, as Google now shows the average latency, total tokens used, and the average cost of using each AI model. Google details <\/a>how it arrived at each metric in documentation around the benchmark. <\/p>\n

Average Latency: Time taken to solve 100 tasks across 10 runs<\/p>\n

Average Total Tokens: Token consumption for a full benchmark run across 10 runs<\/p>\n

Average Cost: Cost per benchmark run at the time of testing in US dollars<\/p>\n

With that in mind, though, we can see that while GPT 5.5 is a bit stronger, it costs over twice as much to perform the same function as Gemini 3.1 Pro. <\/p>\n

Here are the top ten models according to Google, including the new data (as of May 21, 2026):<\/p>\n

ModelScoreAvg LatencyAvg Total TokensAvg CostNew: GPT 5.57415.564.5$133.9GPT 5.472.421.264.2$91.7Gemini 3.1 Pro Preview72.411.575.4$49.0New: Claude Opus 4.768.711.690.0$124.3GPT 5.3 Codex67.711.271.4$42.6Claude Opus 4.666.69.969.5$84.4GPT 5.2 Codex62.524.3124.4$121.9Claude Opus 4.561.912.579.8$102.5Gemini 3 Pro Preview60.49.8117.0$63.7New: GLM 5.159.733.480.2$46.7<\/p>\n

As mentioned, there are more open-weight models now in the rankings, including Gemma, Qwen, DeepSeek, MiMo, and more. Of these, GLM 5.1 scored the highest, followed by Kimi K2.6.<\/p>\n

You can see the full rankings on Google\u2019s website<\/a>.<\/p>\n

Google continues to update the \u201cAndroid Bench\u201d on a roughly monthly basis. With Gemini 3.5 Pro coming soon and 3.5 Flash already live, it\u2019ll be interesting to see if Google\u2019s own models can tackle the lead OpenAI has now picked up.<\/p>\n

Are you using an AI models for Android app development? If so, which one?<\/p>\n

More on Android:<\/p>\n

Follow Ben:\u00a0Twitter\/X<\/a>,\u00a0Threads<\/a>, Bluesky<\/a>, and\u00a0Instagram<\/a><\/p>\n

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