{"id":23576,"date":"2026-07-22T00:45:33","date_gmt":"2026-07-21T23:45:33","guid":{"rendered":"https:\/\/innovatenews.site\/index.php\/2026\/07\/22\/google-launches-gemini-3-6-flash-and-3-5-flash-lite-teases-gemini-4\/"},"modified":"2026-07-22T00:45:44","modified_gmt":"2026-07-21T23:45:44","slug":"google-launches-gemini-3-6-flash-and-3-5-flash-lite-teases-gemini-4","status":"publish","type":"post","link":"https:\/\/innovatenews.site\/index.php\/2026\/07\/22\/google-launches-gemini-3-6-flash-and-3-5-flash-lite-teases-gemini-4\/","title":{"rendered":"Google launches Gemini 3.6 Flash and 3.5 Flash-Lite, teases Gemini 4\u00a0"},"content":{"rendered":"
\n

The topic Google launches Gemini 3.6 Flash and 3.5 Flash-Lite, teases Gemini 4\u00a0<\/strong> is currently the subject of lively discussion \u2014 readers and analysts are keeping a close eye on developments.<\/p>\n

This is taking place in a dynamic environment: companies\u2019 decisions and competitors\u2019 reactions can quickly change the picture.<\/p>\n

As we wait for 3.5 Pro, Google today announced Gemini 3.6 Flash and 3.5 Flash-Lite, while providing updates on what comes next.<\/p>\n

Gemini 3.6 Flash follows the last release at I\/O 2026. This update takes into account developer and customer feedback since May by being \u201cmore token efficient across tasks.\u201d<\/p>\n

Compared to 3.5 Flash, it consumes 17% fewer output tokens (per the Artificial Analysis Index), while taking \u201cfewer reasoning steps and tool calls to accomplish multi-step workflows.\u201d At the same time, it\u2019s priced lower at $1.50\/1M input tokens and $7.50\/1M output tokens (versus $9\/1M output).<\/p>\n

In terms of coding performance, Gemini 3.6 Flash \u201cdelivers higher precision with fewer unwanted code edits and reduced execution loops\u201d than its predecessor. Specifically:<\/p>\n

\"\"<\/figure>\n

It generates higher quality and more reliable, production-ready code as seen in DeepSWE (49% vs. 37%), and shows significant improvement in ML Research, as seen in MLE Bench (63.9% vs. 49.7%).<\/p>\n

For knowledge work, the model scores 1421 on GDPval-AA (versus 1349). Computer use capabilities go from 78.4% on OSWorld-Verified to 83%. The knowledge cutoff date finally advances from January 2025 to March 2026.<\/p>\n

The company also announced Gemini 3.5 Flash-Lite for high-throughput and low-latency tasks, like agentic search and document processing. Google says it offers \u201csignificantly better quality than 3.1 Flash-Lite\u201d from March, while pricing is $0.30\/1M input tokens and $2.50\/1M output tokens.<\/p>\n

It\u2019s a significant step up in coding and agentic tasks as seen in Terminal-Bench 2.1 (54% vs 31%), long context as seen in GDM-MRCR v2 (72.2% vs. 60.1%), and real-world task execution as seen in GDPval-AA v2 (1140 vs. 642).<\/p>\n

Google notes that 3.5 Flash-Lite outperforms 3 Flash: SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%).<\/p>\n

\"\"<\/figure>\n

The final announcement today is Gemini 3.5 Flash Cyber for finding and fixing security vulnerabilities. Flash serves as the foundation given its performance and efficiency, with the goal of detecting, validating, and patching \u201ccode security issues at scale\u201d and at a \u201clower price per token than larger models.\u201d<\/p>\n

Google\u2019s CodeMender tool uses multiple 3.5 Flash Cyber agents. Access is initially for governments and trusted partners \u201cas part of a limited-access pilot program.\u201d<\/p>\n

This will give frontline defenders a head start in finding and fixing critical vulnerabilities before they can be exploited, while mitigating against broader misuse.<\/p>\n

Gemini 3.6 Flash and 3.5 Flash-Lite are available today in the Gemini app, with the latter model also coming to Search. Developers can access them through Google Antigravity, AI Studio, and Android Studio.<\/p>\n

Looking ahead, Google reiterates that \u201cGemini 3.5 Pro is currently testing with partners,\u201d with broad availability \u201cas soon as it\u2019s ready.\u201d<\/p>\n

Meanwhile, the DeepMind team is \u201calready focusing on building the next generation of models.\u201d<\/p>\n

We have already started our most ambitious pre-training run yet, for Gemini 4, and can\u2019t wait to share more.<\/p>\n