Google Unveils Gemini 3.6 Flash, Cybersecurity AI, and Delays 3.5 Pro

Google announced a significant evolution of its AI models at I/O in May with the release of Gemini 3.5 Flash, and it’s not slowing down. The company revealed three new AI models today, including its first version of Gemini geared toward cybersecurity. However, none of the new models is the delayed Gemini 3.5 Pro, which was supposed to launch in June.

Gemini 3.5 Flash, which was the star of the show at I/O, has already been deprecated. In its place, developers and users will find Gemini 3.6 Flash. Google makes the usual claims about this model—it’s marginally more capable and better at coding, and it has great multimodal features.

Google says the changes to 3.6 Flash were made in response to user feedback on the 3.5 release. In general, Gemini 3.5 Flash didn’t appear to live up to Google’s promises around code generation. Perhaps that is simply a consequence of Google’s intense focus on efficiency as businesses have started to fret over the cost of AI tokens.

In the DeepSWE test for coding, 3.6 Flash jumps to 49 percent versus 37 percent for 3.5 Flash. The new model now supports computer use as a standard feature in the Gemini API, too. The OSWorld test for computer use shows a modest boost to 83 percent from 3.5’s 78.4 percent score. Efficiency was a big focus for Gemini 3.5 Flash, and Google says that effort has been amped up with 3.6. Even with small benchmark gains, Gemini 3.6 Flash uses about 17 percent fewer tokens.

In agentic workflows (like the one below), Gemini 3.6 Flash should complete tasks more accurately, in fewer steps, and with fewer tokens. That could save developers (and Google) a lot of money. The new model has a lower API cost, at $1.50/1M input tokens and $7.50/1M output tokens. It was $1.50 and $9, respectively, for 3.5 Flash.

Google is not done with the 3.5 branch yet, though. It has also released Gemini 3.5 Flash Lite and 3.5 Flash Cyber. The new Flash Lite is Google’s most efficient modern AI, hitting an impressive 350 tokens per second. The company claims this model is ideal for scaling agentic systems without breaking the bank. Based on benchmark numbers, the new Flash Lite is almost on par with frontier models from about a year ago, but it’s cheap. Pricing is set at $0.30/1M input tokens and $2.50/1M output tokens, though that is slightly higher than the previous 3.1 Flash Lite ($0.25 and $1.50).

Gemini 3.6 Flash will begin rolling out in the API today, and it will take over from 3.5 Flash in the Gemini app. Likewise, Gemini 3.5 Flash Lite is available to developers and in the Gemini app. Google also notes that you’ll see a lot of 3.5 Flash Lite in Google search, where its higher speed probably makes it ideal for AI Overviews. So those may get a smidge better.

Google’s AI roadmap

Google also has some news on upcoming AI models. First up will be a limited release of Gemini 3.5 Flash Cyber. This is Google’s first LLM tuned specifically for cybersecurity. The company says this model is almost as good at finding and fixing cybersecurity issues as the much larger and more expensive Claude Mythos. At the same time, it has the efficiency of a Flash model.

Of course, Google acknowledges the “dual-use” nature of such models, which can just as easily be used to identify vulnerabilities for malicious purposes. The company borrows a page from Anthropic here, painting Gemini 3.5 Flash Cyber as too dangerous to release publicly. Instead, the model will launch soon as a limited pilot in Google DeepMind’s CodeMender agent, which is available exclusively to trusted partners and governments.

Then there’s the curious case of Gemini 3.5 Pro, which Google claimed was slated for a June release back at I/O. That never happened, and Google hasn’t had anything to say about it until now. There’s not much of an update, though. The company claims its new flagship model, which is supposed to rival GPT 5.6 and Claude Fable/Sonnet 5, is currently in testing with unnamed partners. The model will be released “as soon as it’s ready.” Earlier reports claimed that Google delayed 3.5 Pro because it couldn’t match competing models in coding.

Gemini 3.5 Flash may not be top-of-the-line for long when it arrives. Google also notes that it has started pre-training for Gemini 4, a process that is apparently more ambitious than its previous AI efforts. There’s no timeline for when we’ll see Gemini 4, and we don’t know if there will be more 3.x releases before that.